Applications

Explore high-precision calibration for FOG IMU (Fiber Optic Gyro Inertial Measurement Unit) across full temperature ranges. Learn key error modeling techniques, 3D bidirectional rate/one-position calibration, and Piecewise Linear Interpolation (PLI) compensation for enhanced navigation accuracy in drones, autonomous vehicles, and robotics. How can FOG IMU (Inertial Measurement Unit based on Fiber Optic Gyroscope) maintain high precision in complex temperature environments? This article comprehensively analyzes its error modeling and compensation methods. 1. Introduction to FOG IMU: The "Brain" of Flight Navigation System In modern aircraft, especially in small rotor unmanned aerial vehicle systems, FOG IMU is the core component of the navigation information and attitude measurement system. The fiber optic gyroscope (FOG) based on the Sagnac effect has advantages such as high precision, strong shock resistance, and fast response, but it has poor adaptability to temperature changes. This can easily lead to measurement errors during the flight process where the dynamic environment changes drastically, thereby affecting the performance of the overall navigation system. 2. Error Sources: Analysis of Common Measurement Deviations of FOG IMU The errors of FOG IMU can be mainly classified into two types:(1) Angular velocity channel error: This includes installation error, proportional factor error, zero bias error, etc. (2) Acceleration channel error: Mainly caused by installation error, temperature drift and dynamic disturbance. These errors accumulate in the actual environment, seriously affecting the stability and accuracy of the flight control system. 3. Limitations of Traditional Calibration Methods Although traditional static multi-orientation calibration and angular velocity method can partially address the issue of errors, they have obvious shortcomings in the following aspects:(1) Unable to balance accuracy and computational efficiency(2) Inapplicable to full temperature range compensation(3) Dynamic disturbances affect the stability of calibrationThis requires a more intelligent and efficient error modeling and temperature compensation mechanism. 4. Detailed Explanation of the Three-Dimensional Positive and Negative Speed/One-Axis Attitude Calibration Method in the Full Temperature Range (1) Precise Calibration at Multiple Temperature PointsBy setting multiple temperature points ranging from -10°C to 40°C and conducting three-axis rotation calibration at each point, temperature-related error parameters can be collected.(2) Three-Dimensional Positive and Negative Speed Method: Precisely Simulating Real Flight ConditionsUsing a single-axis rate turntable and a high-precision hexahedral tool, positive and negative speed calibration in the X/Y/Z axis directions can be achieved, enhancing the system's adaptability to dynamic environments.(3) One-Axis Attitude Stabilization: Quickly Capturing System Zero OffsetWhile maintaining a static state, initial offsets under different temperatures are recorded to provide precise data support for subsequent error modeling. 5. Piecewise Linear Interpolation (PLI): A Precise Error Compensation Tool with Low Computational Load To meet the error compensation requirements of FOG IMU across the entire temperature range, this paper proposes the Piecewise Linear Interpolation algorithm (PLI), which has the following characteristics:(1) Low computational load: Suitable for embedded navigation systems with limited resources(2) Strong real-time compensation capability: Error is dynamically adjusted with temperature changes(3) Easy to deploy and upgradeCompared with the high-order least squares method, the PLI scheme ensures the compensation accuracy while significantly reducing the system's computational burden, making it suitable for real-time computing scenarios during flight. 6. Practical Verification: Outstanding Performance in Complex Flight Environments Through on-board field experiments, this method significantly enhanced the measurement accuracy and environmental adaptability of the system under various temperatures and dynamic disturbances, providing a solid navigation foundation for subsequent high-performance small rotorcraft flight platforms. 7. Conclusion: Mastering the error modeling and compensation of FOG IMU is the key to building a highly reliable flight platform. With the development of unmanned aerial vehicles and intelligent flight systems, the requirements for the accuracy of navigation systems have become increasingly stringent. By introducing the three-position positive and negative speed calibration and segmented linear interpolation compensation methods, the adaptability and accuracy of FOG IMU in the full temperature range and strong dynamic environment can be significantly improved. In the future, this technology is expected to play a greater role in autonomous driving, robot navigation, and high-precision map collection and other fields. Micro-Magic’s U-F3X80, U-F3X90, U-F3X100,and U-F300 , we can use full-temperature three-way positive and negative rate/one position calibration and PLI compensation method. According to the error characteristics of fiber optic gyro and quartz flexible accelerometer, the FOG inertial measurement unit error model is established, and the three-bit positive and negative rate/one-position calibration scheme is designed at each constant temperature point. The PLI algorithm is used to compensate the zero bias and scale factor temperature errors of the system in real time, reducing the calibration workload and the calculation amount of the compensation algorithm, and improving the system dynamics, temperature environment adaptability and measurement accuracy. U-F3X80 Fiber Optic Gyroscope IMU U-F100A Middle Precision Fiber Optic Gyroscope Based IMU U-F3X100 Fiber Optic Gyroscope IMU U-F3X90 Fiber Optic Gyroscope IMU  

Learn how to reduce magnetic sensitivity in FOG IMUs with advanced techniques like depolarization, magnetic shielding, and error compensation. Discover high-precision solutions for aviation and navigation systems. In high-precision inertial measurement units (IMUs), the fiber optic gyroscope (FOG) is one of the core components, and its performance is crucial for the positioning and attitude perception of the entire system. However, due to the Faraday effect of the optical fiber coil, FOG is extremely sensitive to magnetic field anomalies, which directly leads to the degradation of its zero bias and drift performance, thereby affecting the overall accuracy of the IMU. So, how is the magnetic sensitivity of FOG IMU generated? And how can this influence be effectively suppressed? This article will deeply analyze the technical paths to reduce the magnetic sensitivity of FOG from the perspective of theory to engineering practice. 1. FOG Magnetic Sensitivity: Starting from the Physical Mechanism The reason why FOG is sensitive to magnetic fields lies in the Faraday effect - that is, when linearly polarized light passes through a certain material, under the influence of a magnetic field, its polarization plane will rotate. In the Sagnac ring interference structure of FOG, this rotational effect will cause a phase difference between two beams propagating in opposite directions, thereby leading to measurement errors. In other words, the interference of magnetic fields is not static but dynamically affects the output of FOG in a drifting manner.Theoretically, an axial magnetic field perpendicular to the axis of the optical fiber coil should not trigger the Faraday effect. However, in reality, due to the slight inclination during the winding of the optical fiber, the "axial magnetic effect" is still triggered. This is the fundamental reason why the influence of magnetic fields cannot be ignored in high-precision applications of FOG. 2. Two major technical approaches to reducing FOG magnetic sensitivity (1) Improvements at the optical device level a. Depolarization technology By replacing polarization-preserving fibers with single-mode fibers, the magnetic field response can be reduced. Because single-mode fibers have a weaker response to the Faraday effect, the sensitivity is reduced at the source.b. Advanced winding processControlling the winding tension and reducing residual stress within the fibers can effectively reduce magnetic induction errors. Combined with an automated tension control system, it is the key to improving the consistency of polarization-preserving coils.c. New low-magnetic-sensitivity optical fibersAt present, some manufacturers have launched optical fiber materials with low magnetic response coefficients. When used in combination with ring structures, they can optimize the magnetic anti-interference ability at the material level. (2) System-level Anti-magnetic Measures a. Magnetic Error Modeling and CompensationBy installing magnetic sensors (such as flux gates) to monitor the magnetic field in real time and introducing compensation models in the control system, the output of FOG can be dynamically corrected.b. Multi-layer Magnetic Shielding StructureUsing materials such as μ-alloys to construct double-layer or multi-layer shielding cavities can effectively weaken the influence of external magnetic fields on FOG. Finite element modeling has confirmed that its shielding efficiency can be increased by tens of times, but it also increases the system weight and cost. 3. Experimental Verification: How significant is the influence of magnetic fields? In a set of experiments based on a three-axis turntable, researchers collected the drift data of FOG in both open and closed states. The results showed that when the magnetic field interference was enhanced, the drift amplitude of FOG could increase by 5 to 10 times, and obvious spectral interference signals (such as 12.48Hz, 24.96Hz, etc.) appeared.This further indicates that if no effective measures are taken, the accuracy of FOG will be greatly compromised in actual aviation, space, and other high electromagnetic environments. 4. Practical Recommendations: How to Enhance the Anti-Magnetic Capability of FOG IMU? In practical applications, we recommend the following combination strategies:(1) Select polarization-eliminating FOG structure(2) Use low-magnetic-response optical fibers(3) Introduce optical fiber winding equipment with automatic tension control(4) Install three-dimensional flux gates and build error models(5) Optimize the design of μ-alloy shielding shellsTaking the U-F3X80, U-F3X100 series launched by Micro-Magic as examples, the integrated optical gyroscopes inside them have maintained stable output even in the presence of magnetic interference through multiple technical improvements, making them the preferred solution among current aviation-grade IMUs.  5. Conclusion: Accuracy determines the application level, and magnetic sensitivity must be taken seriously In high-precision positioning, navigation and guidance systems, the performance of FOG IMU determines the reliability of the system. And magnetic sensitivity, as a problem that has been overlooked for a long time, is now becoming one of the "bottlenecks" of accuracy. Only through collaborative optimization from materials, structures to system level can we truly achieve high-precision output of IMU in complex electromagnetic environments. If you are confused about IMU selection or FOG accuracy issues, you might as well rethink from the perspective of magnetic sensitivity. Micro-Magic’s FOG IMU U-F3X80, U-F3X90, U-F3X100,and U-F300 are all composed of fiber optic gyroscopes. In order to improve the accuracy of FOG IMU, we can completely reduce the magnetic sensitivity of the fiber optic gyroscopes inside them by corresponding technical measures. U-F3X80 Fiber Optic Gyroscope IMU U-F3X90 Fiber Optic Gyroscope IMU U-F100A Middle Precision Fiber Optic Gyroscope  U-F3X100 Fiber Optic Gyroscope IMU      

Discover the mid-low precision FOG IMU system: a cost-effective, shock-resistant inertial navigation solution for UAVs, robotics, and marine applications. Learn about its modular design, quick startup, and high stability. In the fields of unmanned systems, intelligent manufacturing, and precise control, the inertial measurement unit (IMU) is becoming a crucial "invisible technology". Today, we will take you to deeply understand a solution that performs well in actual projects - a mid-low precision FOG IMU system designed based on open-loop fiber optic gyroscope (FOG) and MEMS accelerometer.This is not only an inertial sensing device, but also a perfect balance between miniaturization, high cost-effectiveness, and precise navigation. 1. Why Choose FOG IMU? As the traditional platform-based inertial navigation systems are gradually fading from the historical stage, strapdown inertial navigation systems (SINS) have become mainstream relying on mathematical modeling and digital computing.So, what are the core advantages of FOG IMU?(1) Resistance to shock and interference: Fiber optic gyros are naturally shock-resistant and can withstand high G forces, making them particularly suitable for harsh environments.(2) Quick startup: No need for complex initialization; plug and play once powered on.(3) Precise and cost-effective: While meeting navigation requirements, it also controls costs.(4) Easy integration: Small size, low power consumption, and easy embedding.Therefore, it is widely applied in fields such as unmanned aerial vehicles, robots, vehicle-mounted systems, and maritime navigation. 2. Highlights of System Architecture This FOG IMU adopts a modular design, consisting of a three-axis fiber optic gyroscope, a three-axis MEMS accelerometer, a data acquisition module, and a high-speed DSP, supplemented by temperature compensation and error modeling algorithms, to achieve stable output.The six sensitive axes are arranged in three-dimensional orthogonal manner, combined with a software compensation mechanism, to eliminate the influence of structural errors on navigation accuracy.Moreover, this system has also been verified through simulation, ensuring that it still meets the required accuracy for navigation calculations even when using low-precision sensors. 3. Data Acquisition Module: The "Neural Center" of IMU We have specially optimized the data acquisition link:(1) Analog signal conditioning: Two-stage amplification + analog filter, enhancing signal clarity.(2) High-precision ADC sampling: 10ms update cycle, ensuring rapid system response.(3) Temperature compensation channel: Integrated chip and environmental temperature monitoring, achieving full environmental adaptability.This module plays a crucial role in enhancing the overall accuracy of the system. 4. Performance and Real-World Feedback After the prototype deployment and system testing, the performance of this FOG IMU system is as follows:(1) Excellent stability of attitude angles(2) Static errors within the controllable range(3) Strong anti-interference performance, capable of adapting to rapid dynamic changesCurrently, this system has been put into use in a certain type of robot navigation platform, and the feedback is consistent and good. 5. Application Domain Outlook The FOG IMU system is ready to be applied in the following scenarios:(1) Navigation for unmanned aircraft and unmanned vehicles(2) Marine measurement systems(3) Industrial automation equipment(4) Attitude control for low-orbit satellites(5) Intelligent robots and precise positioningIn the future, we will also launch an upgraded version of the FOG IMU tailored for high-precision requirements such as UF-100A. Stay tuned for more updates!   UF100A Middle Precision Fiber Optic Gyroscope Based IMU    

"An in-depth analysis of the testing methods for the bias (zero bias) and scale factor of quartz flexible accelerometers is provided, including specialized techniques such as four-point rolling test and two-point test, as well as the calculation formula for temperature sensitivity. This is applicable to high-precision applications such as inertial navigation and spacecraft."   The bias (zero bias) and scale factor of quartz flexible accelerometers directly determine the measurement accuracy and long-term stability of the accelerometer, especially in high-precision application scenarios such as inertial navigation and attitude control. Therefore, they are two key performance indicators for evaluating quartz accelerometers.   The core significance of bias (zero bias) lies in its inherent system error of the accelerometer, which directly leads to the fundamental deviation of all measurement results. For example, if the zero bias is 1 mg, the measured value will add this error regardless of the actual acceleration. Zero bias will also drift with factors such as time, temperature, and vibration (zero bias stability). In inertial navigation systems, zero drift is continuously amplified through integration operations, resulting in cumulative errors in position and velocity. The temperature characteristics of quartz materials can also cause zero bias to change with temperature (zero bias temperature coefficient), so temperature compensation algorithms are needed to suppress this effect in high-precision applications. Scale factor refers to the proportional relationship between the output signal of an accelerometer and the actual input acceleration. The error in scale factor can directly lead to proportional distortion of the measurement results. The stability of scale factor directly affects system performance in high dynamic range or variable temperature environments. In the acceleration integration operation of inertial navigation, the scale factor error will be integrated twice, further amplifying the position error.   Therefore, the reason why bias and scale factor have become key performance indicators of quartz flexible accelerometers is that they are both fundamental error sources and key constraints on long-term stability. In system level applications, the performance of these two directly determines whether the accelerometer can meet the requirements of high precision and high reliability, especially in scenarios such as unmanned driving, spacecraft, submarine navigation, etc. where there is zero tolerance for errors   The bias test can be conducted through two methods: four point rolling test (0°，90°，180°，270°positions) or two-point test (90°，270°positions). The scale factor test can be conducted through three methods: four point rolling test (0°，90°，180°，270°positions), two-point test (90°，270°positions), and vibration test. Taking the four-point rolling test method as an example, this article explains how to obtain the bias and scale factor of an acceleration sensor.     1. Testing methods for bias and scaling factors:   a) Install the accelerometer on a specific test bench (multi tooth indexing head). b) Start the test bench c) Rotate the test bench clockwise to the 0°position, stabilize it, and record the output of multiple sets of tested products according to the specified sampling frequency. Take the arithmetic mean as the measurement result; d) Rotate the test bench clockwise to the 90°position, stabilize it, and record the output of multiple sets of tested products according to the specified sampling frequency. Take the arithmetic mean as the measurement result; e) Rotate the test bench clockwise to the 180°position, stabilize it, and record the output of multiple sets of tested products according to the specified sampling frequency. Take the arithmetic mean as the measurement result; f) Rotate the test bench clockwise to the 270°position, stabilize it, and record the output of multiple sets of tested products according to the specified sampling frequency. Take the arithmetic mean as the measurement result; g) Rotate the test bench clockwise to the 360°position, then counterclockwise to make the rotation angles at 270°, 180°, 90°, and 0°positions. After stabilization, record the output of multiple sets of tested products according to the specified sampling frequency, and take the arithmetic mean as the measurement result. h) Calculate the bias and scaling factor of the tested product using the following formula (1) and (2). K0 =    -------------------------------------- (1)   K1 =   -------------------------------------- (2)        Where:         K0 -------Bias         K1 -------Scale factor         -------The total average of forward and reverse readings at 0°position         -----The total average reading of forward and reverse rotation at 90°position         --- The total average reading of forward and reverse rotation at180° position         --- The total average of readings for forward and reverse rotation at 270°position   2. Test method for bias temperature sensitivity and scale factor temperature sensitivity a) Start the test bench b) Calculate the bias and scaling factors at each temperature point using the formulas (1) and formulas (2) at room temperature, the upper limit operating temperature specified by the accelerometer, and the lower limit temperature specified by the accelerometer. c) Calculate the temperature sensitivity of the accelerometer using the following formula (3) and (4):      ---------------------(3) where： ---- Bias temperature sensitivity ----Bias of upper limit temperature of sensor ----Bias of sensor room temperature -----Bias of the lower limit temperature of the sensor ------Upper limit temperature ------Room temperature -------Lower limit temperature        ---------------------(4) Where: ----Scale factor temperature sensitivity ------Scale factor ----Scale factor for the upper limit temperature of the sensor ----Scale factor of sensor room temperature -----Scale factor for the lower limit temperature of the sensor ------Upper limit temperature ------Room temperature -------Lower limit temperature AC-1 Quartz Flexible Accelerometer   AC-4 Quartz Flexible Accelerometer  

Electronic compass (also known as digital compass), is through the measurement of the Earth's magnetic field to complete the course calculation, often as a GPS signal or network is not effective supplement. Based on its advantages of small size, low energy consumption, high precision and miniaturization, it is widely used in the field of magnetic heading measurement such as UAV, Marine and automobile. However, in use, the electronic compass also has its own inherent defects: easy to be affected by external magnetic field interference and error, which is the main reason for affecting its measurement accuracy and restricting its application, so it is very necessary to study the method of compensating the measurement error of the electronic compass.   At present, there are many methods to compensate measurement error. For example, the compensation coefficient method is mainly aimed at the dynamic interference during measurement, while the static interference compensation effect is little, and the application range is small. Another example is the adaptive compensation method, which requires the system to achieve high compensation accuracy in the case of linear or low-speed movement, if the system rotates faster, the measurement accuracy will be greatly affected, so the more demanding application scenario makes this method not extensive. At present, if only a single error compensation model is used to compensate the compass error, it can not meet the requirements of the measuring system. In this paper, an error compensation algorithm based on ellipse hypothesis is proposed, which integrates the principle of least squares. The algorithm can realize effective compensation for the measuring error of the electronic compass, and has the characteristics of moderate calculation and wide application. 1.Error analysis of magnetic heading system When the digital compass is installed in the carrier for magnetic heading measurement, its measurement error is caused by a variety of factors, which can be roughly divided into two categories: one is caused by the system's own structure, materials, assembly and other reasons, including compass, installation error, manufacturing error; The other is attitude signal error, although it does not belong to the heading measurement system itself, but it is involved in the calculation of heading parameters, will also cause measurement error. Because the compass error is the most difficult to control and has the greatest influence on the course accuracy, this paper mainly analyzes the compass error. The compass difference is mainly composed of the horizontal component of the hard iron magnetic field and the horizontal component of the soft iron magnetic field of the carrier. A large number of experimental studies show that the error caused by the hard ferromagnetic field on the moving carrier is a periodic error, which can be expressed by formula (1), and its rule is approximately sinusoidal curve; The error caused by the soft iron magnetic field can be expressed by formula (2), and the law changes with the change of the environmental magnetic field.   Where ϕi is the measurement of the heading Angle, and A, B, C, D, and E are error coefficients. Through the error analysis of the compass above, we can see that the total compass of the electronic compass should be the algebraic sum of the above errors. Therefore, combine formulas (1) and (2) to find the total difference ∆ϕ     2.Error compensation by least square method Least Squares (LS) can be used to find the best function match of data by minimizing the sum of squares of errors. It is easy to obtain unknown data and minimize the sum of squares of errors between it and the actual data. The least squares method can also be used for curve fitting and is often used for data optimization.   The least square method can optimize the data fitting in the sense of minimum square variance. It is a mathematical optimization method that can compensate the error caused by the magnetic field interference of the external environment. Under normal circumstances, the measurement error presents a certain periodicity, a more suitable fitting method can be used trigonometric function method, based on the mathematical model of Fourier function, and then corrected according to the heading parameters provided by the standard compass. The following is a brief introduction to the basic principles of least squares.   When a correspondence between two variables y and x needs to be determined based on observations, assuming that they are linear, y at time t can be expressed as:   Where H1,H2,... Hn is n unknown parameters to be determined, x1 (t), x2(t),... xt(t) is a known deterministic function, such as the sine and cosine function of t. Let's say at time t1,t2... tn makes m measurements of y and x, hoping that the variables y and x1 (t), x2(t),... xt(t) to estimate their values. Then formula (4) can be expressed in matrix form: Y =X*H   Using the least squares method, the least squares estimates of the error coefficients A, B, C, D and E shown in formula (3) are obtained from the known azimuth Angle measurement ϕi and azimuth Angle error ∆ϕ. The specific calculation steps are as follows: ① The eight-position error measurement method is adopted. Taking into account the number of samples, the amount of data calculation and the measurement accuracy, eight points with the same Angle interval within the range of heading Angle 360, such as 0, 45, 90, 135, 180, 225, 270 and 315, were taken to conduct heading error test, and 8 sets of data were obtained. ② The error coefficients A, B, C, D and E are obtained according to the principle of least squares. Through the previous analysis, when the error coefficients A, B, C, D and E are calculated by the least square method, the actual course of the carrier after error correction can be calculated by the calculation formula, and the specific research and analysis will not be done here.   3.Summary Micro-Magic company specializes in navigation products, in addition to the least method of error compensation, there are elliptic false method of error compensation and other compensation methods. In the research and development process of electronic compass, it has gradually mature technology and consolidated theoretical foundation. In addition to the continuous optimization of north finding accuracy, there are tilt compensation and other functions, if you are interested in our products, welcome to learn more about our low-cost 2D digital compass C9-C, and 40° tilt compensation - 3D digital compass C90-B and so on, you can contact our professional and technical staff at any time. C9-A High-precision 3 dimension electronic compass with advanced 3D compensation technology C9-B Modbus RTU mode two dimension (2D) electronic compass for unmanned aerial vehicles C9-C high-precision two-dimensional (2D) electronic compass single circuit board measuring azimuth angles from 0 to 360 deg C9-D High-Precision Two-Dimensional (2D) Electronic Compass Single Circuit Board Measuring Azimuth Angles From 0 To 360 Deg    

    Electronic compass has its own unique advantages: the electronic compass itself is small in size, light in weight, the acquisition and solution of azimuth information is real-time, and the output digital signal can make it more direct and convenient in the subsequent use. At present, the development of digital compass sensor technology has been relatively mature, so that it has certain advantages in measurement accuracy and manufacturing cost. Because digital compass is widely used in practice, a large number of high-precision, low-cost electronic compass products suitable for large-scale industrialization need to be put into production.    In today's society, the design and research of navigation and orientation instruments have important value and significance. With the expansion of human exploration in the space field, the stability maintenance, tracking guidance and other functions of artificial satellites, space shuttles, missile weapon systems and various platforms all need the support of navigation orientation technology and corresponding attitude adjustment devices. To sum up, obtaining orientation information and realizing the corresponding attitude control play a fundamental role in various scientific research and engineering realization.   According to the characteristic that the geomagnetic field changes little in a certain time range, it can be considered that the geomagnetic information at the same place is fixed in a short time, and the azimuth information such as heading Angle and attitude Angle can be calculated by the electronic compass according to the geomagnetic intensity information measured.   1.The principle characteristics of the geomagnetic field   As the basic physical quantity of the earth, the geomagnetic field has a direct effect on the physical characteristics of electric and magnetic substances in the earth environment. The characteristics of the Earth magnetic vector field provide a basic coordinate system for azimuth information, and the use of geomagnetic information navigation is stable and reliable, without receiving external information, with good concealment. The geomagnetic field is generated from the structure of the earth itself. There are many magnetic elements and substances in the earth's interior, which produce free flowing electrons under the influence of the extreme environment inside the Earth. These free electrons lead to the improvement of the conductivity between the earth's inner core and outer core, resulting in the flow and movement of free electrons between different strata. This makes the earth as a whole have a stable magnetic field on a macro level, which is equivalent to a magnetic dipole with a constant magnetic field existing in the center of the Earth, resulting in the production of north and south magnetic poles. Figure 1 shows the schematic diagram of the distribution of the Earth's magnetic field. The unit of magnetic induction intensity is Tesla (T), which is Gaussian (Gs) in Gaussian units, and the corresponding relationship between the two is 1T=10-4Gs, the unit system of magnetic field intensity is A/m, and the unit system of magnetic field intensity is Oster (Oe) in Gaussian units, and the corresponding relationship between the two is 1A/m=4π*10-3Oe   The Earth's magnetic field can be classified into basic geomagnetic field, variable geomagnetic field and abnormal geomagnetic field according to the degree of stability. The basic magnetic field covers most of the magnetic field, accounting for more than 90% of the Earth's total magnetic field. The basic type of geomagnetic field can also be divided into dipole-induced magnetic field and non-dipole-induced magnetic field, in which the dipole-induced effect accounts for the main part, the magnetic field comes from the circulation movement of iron and nickel under high temperature and high pressure environment, and the non-dipole is mainly generated by the self-excited motor effect. The basic geomagnetic field itself also changes, but the period of change is very long, so the Earth's magnetic field as a whole can be considered stable. The changing electromagnetic field is generated in the ionosphere and magnetosphere of the earth, and the magnetic field disturbance is mainly related to the solar change, and the changing electromagnetic field can be divided into stable change and interference change. Quiet changes occur on the solar or lunar calendar and are mainly caused by solar electromagnetic radiation or particle radiation. The phenomenon of magnetic storm is the phenomenon of geomagnetic interference in large space, the main effect of which is the strong change of the ground vector component of geomagnetic field. The abnormal geomagnetic field comes from the ferromagnetic properties of ferromagnetic materials and can be regarded as the constant vector addition on the stable geomagnetic field.   2.Error analysis of electronic compass   Deviation of electronic compass, also known as compass deviation, is the error of measurement results caused by ferromagnetic interference in the nearby environment when the compass is working. The deviation between the measurement results and the real value is even tens of degrees without corresponding compensation link, which is because the magnetic field strength of the earth magnetic field is weak, and the magnetic field strength is only 0.5-0.6 gauss. Therefore, the measurement results of digital compass are very easy to introduce the interference caused by environmental ferromagnetic factors, and the compass has become the main source of error of electronic compass.   Compass can also be divided into hard iron interference and soft iron interference, hard iron interference is caused by permanent magnetic objects or magnetized objects, with a permanent magnetic material under the influence of the external magnetic field, the overall magnetic moment of the object is no longer zero, thus showing magnetism. The magnetic field strength generated by it can be regarded as constant and unchanged in a certain time range, and this permanent magnetic material still maintains a relatively stable residual magnetic field strength after the magnetization effect, even after the external magnetic field action is removed. To sum up, the position and intensity of the interference effect on the compass can be considered as a fixed and constant stabilizing effect, and the compensation means for it is relatively easy to realize.   Summary     Micro-Magic company for aerospace, mining drilling and other engineering projects to provide tools and technical support, the current electronic compass series, C9000-A,C9000-B,C9000-C,C9000-D and other products, with soft magnetic, hard magnetic compensation function, it plays an important role in improving the north finding accuracy. If you want to understand the information of digital compass, you can always communicate with our professionals. C9000-A Tilt Compensated Magnetic Compass Sensor 3 Axis Magnetic Heading Yaw Angle Meter C9000-B High-precision all attitude 3D electronic compass board using advanced hard and soft iron calibration algorithms digital output C9000-C Fluxgate Compass Gyro Compensated Compass 6 Axis Compass Electronic Yaw Heading Sensor C9000-D High Performance Heading Sensor for Antenna Tower Azimuth Finding Low Cost Azimuth Angle Sensor Measure Tower Heading Angle  

Key Points   Product: Electronic Compass (C9000-B and other variants)Features:• Utilizes three-dimensional magneto-resistive sensors for geomagnetic field measurement• Incorporates an accelerometer for static stability and inclination compensation• Uses Kalman filtering algorithm for noise reduction and optimal state estimation• Provides digital output signal for direct integration with control systemsAdvantages:• High accuracy and stability, suitable for dynamic environments• Low energy consumption, compact size, and lightweight• Anti-shaking and anti-vibration, ideal for aviation, robotics, autonomous vehicles, and navigation systems• Capable of compensating for hard and soft magnetic interference• Can be integrated into control loops for applications like autonomous navigation or equipment maintenance Electronic compasses, also called digital compasses, are a method of using the Earth's magnetic field to determine the North Pole, and have been widely used as navigation instruments or attitude sensors. In ancient times, it was called compass, and the magneto-resistance sensor produced by modern advanced processing technology provides a powerful help for the digitalization of compass. Nowadays, electronic compasses are generally machined from chips such as magneto-resistive sensors or fluxgates. It can be used in horizontal and vertical hole measurement, underwater exploration, aircraft navigation, scientific research, education and training, building positioning, equipment maintenance, navigation system and other fields.   Compared with the traditional pointer type and balance frame structure compass, the digital compass has low energy consumption, small size, light weight, high precision and miniaturization. Its output signal can be digitally displayed through processing. It can not only be used for pointing, but also the digital signal can be directly sent to the automatic rudder to control the ship's operation. At present, the three-axis strap-down magnetic resistance digital magnetic compass is widely used. This kind of compass has the advantages of anti-shaking and anti-vibration, high heading accuracy, electronic compensation for interference field, and can be integrated into the control loop for data link, so it is widely used in aviation, aerospace, robotics, navigation, vehicle autonomous navigation and other fields.   1.The constitution of an electronic compass The three-dimensional electronic compass C9000-B is composed of a three-dimensional reluctance sensor, an inclination sensor and an MCU. The 3D magneto-resistive sensor is used to measure the earth's magnetic field, and the inclination sensor is used to compensate the non-horizontal state of the magnetometer. The MCU processes signals from magnetometers and tilt sensors as well as data output and soft and hard iron compensation. The magnetometer is based on three vertical magneto-resistive sensors, each axial sensor detects the strength of the geomagnetic field in that direction.     The sensor in the forward direction called the x direction detects the vector value of the geomagnetic field in the x direction, and the sensor in the right or Y direction detects the vector value of the geomagnetic field in the Y direction. Sensors in the down or Z direction detect the vector value of the Earth's magnetic field in the Z direction.   The sensitivity of the sensors in each direction has been adjusted to the optimum point based on the component vector of the geomagnetic field in that direction and has very low cross-axis sensitivity. The analog output signal generated by the sensor is amplified and sent to MCU for processing.   2.The following part of the hardware and principles are introduced 1)Magnetometer: Since the geomagnetic field is a vector, at a certain point, this vector can be broken down into two components parallel to the local level and one component perpendicular to the local level. So if you keep the compass module parallel to the local level the three axes of the magnetometer correspond to these three components. At present, the module is parallel to the horizontal plane by the Angle compensation, and then the heading Angle is calculated by the compensated data.   2) Accelerometer: The acceleration can be calculated from the three-axis data, which has advantages in static stability.   3)Kalman filtering is an algorithm that optimally estimates the state of a system by using linear system state equation and observing system input and output data. Since the observation data includes the effects of noise and interference in the system, the optimal estimation can also be regarded as a filtering process.   In radar, for example, one is interested in tracking a target, but measurements of the target's position, speed, and acceleration are often noisy at all times. Kalman filter uses the dynamic information of the target, tries to remove the influence of noise, and gets a good estimate of the target position. This estimate can be an estimate of the current target location (filtering), an estimate of the future location (prediction), or an estimate of the past location (interpolation or smoothing).   Summary In addition to the three-axis electronic compass, Micro-Magic company has a wealth of electronic compass types, such as low-cost two-axis electronic compass C9000-B, high-precision two-axis electronic compass C9000-D, etc., they have been strictly tested, in extremely harsh environments can also provide accurate course data. If you have the need for digital compass, freely to contact us. C9000-B High-precision all attitude 3D electronic compass board using advanced hard and soft iron calibration algorithms digital output   C9000-D High Performance Heading Sensor for Antenna Tower Azimuth Finding Low Cost Azimuth Angle Sensor Measure Tower Heading Angle  

Key PointsProduct: Dual Magnetic Sensor Compensation for Electronic CompassFeatures:• Compensates for variable magnetic field interference• Uses dual magnetic sensors for simple, cost-effective calibrationAdvantages:• High fault tolerance and low data collection effort• Suitable for space and budget-constrained platforms• Provides improved heading accuracy in dynamic environments Electronic compass can greatly reduce the interference of the surrounding inherent magnetic field through calibration, and accurately indicate the azimuth Angle, but it is helpless to change the magnetic field interference. During the use of the electronic compass, the proximity of iron and magnetic substances will be avoided as far as possible. However, some electronic compass platforms have variable magnetic field interference from inside the platform, which moves with digital compass. This kind of interference source has the characteristics of fixed relative position and changing magnetic field.   At this time, there are three common technical ways: ① let the changing magnetic field temporarily stop changing or use magnetic shielding materials to isolate interference; ② Find a new way to use dual GPS, AHRS and other systems to indicate the azimuth Angle to avoid the interference of variable magnetic field; ③ The influence of the variable magnetic field interference source on the surrounding magnetic field is measured, and then the azimuth of digital compass is compensated according to the change of the magnetic field. In some use cases, it is not possible to shield the variable magnetic field interference, and due to the limitations of the loading platform, it is not possible to use the dual GPS and AHRS systems that are expensive, heavy and require large space. At this point, the third technical approach becomes the only viable solution.   1.Variable magnetic field interferes with important laws   The magnetic steel and digital compass are fixed in the corresponding position of the test tool, and the reluctance sensor and the Hall sensor with large range are selected for testing respectively. The magnetic sensor is placed in different positions on the tooling, and the readings of the electronic compass and magnetic sensor without magnetic steel and under different magnetic steel attitudes are recorded respectively when the tooling is in different orientations for collation and comparison. It is assumed that G magnetic steel is the change in the reading of a certain axis of the magnetic sensor caused by the change in the attitude of the magnetic steel, that is, the reading of the magnetic sensor when the magnetic steel is present minus the reading of the magnetic steel when the magnetic steel is not present, which represents the influence of the magnetic steel on the magnetic field where the magnetic sensor is located. Through a large number of experiments and summary, it is found that in a certain area, when the magnetic sensor is arranged along the virtual magnetic field line formed by the magnetic steel, there are the following important laws:   (1) Gmagnetic steel rapidly decreases with the increase of distance. For example, at 1cm away from the magnetic steel, G magnetic steel is about ±200000, at 10cm is ±1500, at 20cm is ±200, at 30cm is ±65, at 40cm is ±30. The magnetic readings at the test site were slightly less than ±300.   (2) When the test tool is facing different directions, the G magnetic steel is a fixed value. Figure 1 shows the change rule of G magnetic steel at a distance of 10cm from the magnetic steel, and the horizontal axis shows the orientation of N grade magnetic steel, which is divided into 8 directions. You can see that the four directions of the curve basically coincide. The other two axes of the magnetic sensor also fully conform to this law. When the magnetic steel is in the same attitude, the direction of the magnetic field influence value along the direction of the virtual magnetic induction line formed by the magnetic steel is the same, and the value is proportional to the relationship, that is: Where, G magnetic steel A and G magnetic steel B are two different positions on the virtual magnetic induction line formed by magnetic steel, and the magnetic field change vector caused by the change of magnetic steel attitude. Figure 2~5 shows the change curve of G magnetic steel at 10cm, 20cm and 30cm caused by magnetic steel rotation when the tool is facing north. The horizontal axis is the different posture of the magnetic steel, and the 3 curves represent the x, y and z axes respectively. In the preliminary test, the magnetic sensor was placed manually, and the position error was too large. In subsequent experiments, with the improvement of the accuracy of the magnetic sensor position and navigation attitude, the curve consistency became more obvious, and the law was repeatedly verified. 2.Dual magnetic sensor compensation   According to the above three rules, without considering the interference of other parts of the platform, a test and compensation method based on double magnetic sensors is proposed, which can effectively measure the influence of the attitude change of the magnetic steel on the magnetic field at the position of digital compass. Place A magnetic sensor numbered B near the flux gate of the digital compass (electronic compass three-axis magnetic sensor reading can also be used, that is, digital compass as A magnetic sensor B), and another magnetic sensor numbered A is placed in accordance with the above relationship and easy to install on the platform, keeping the A and B magnetic sensors and digital compass three axes in the same direction. Suppose the output of a magnetic sensor axis in the experiment is   G = Gground+Gmagnetic steel+ Ginterference   Gground and Ginterference are geomagnetic components and environmental interference components of this axis, respectively. Due to the close distance between the two magnetic sensors, in the case of away from external strong magnetic interference can be obtained:   Ginterference A≈Ginterference B，Gground A=Gground B   Where, GA and GB are the readings of the same axis on the magnetic sensor A and B. When the position of A and B magnetic sensors is fixed, the ratio k of their change quantity can be obtained at a constant value. Therefore, the influence component caused by the attitude change of the magnetic steel at the magnetic sensor B, that is, at electronic compass, can be easily obtained according to the above formula.   The above experimental findings and reasoning provide a new way of thinking, using two small and cheap magnetic sensors to calculate the magnetic field changes near digital compass caused by the attitude changes of the magnetic steel in an unusually simple way. Then it is only necessary to study the relationship between this variation and the azimuth offset of digital compass. It is not necessary to calculate the attitude of the magnetic steel according to the change of the magnetic field near the magnetic steel, nor is it necessary to study the complex mapping relationship between the magnetic steel attitude and the azimuth offset of digital compass when the platform is in different azimuth angles, pitch angles and roll angles, which greatly simplifies the calculation process. The data collection workload is greatly reduced.   Summary   In this paper, the calibration and compensation method of dual magnetic sensor based on the proportional relation of specific position is proposed for the fixed variable magnetic field interference source. This method has many advantages such as simple acquisition operation, low cost, convenient use and high fault tolerance. It provides a new idea for calibration compensation of variable field interference sources. For digital compasses, we currently have a wide range, such as the digital output full attitude 3D digital compass C90-A, the high-precision electronic compass C90-B, and the low-cost electronic compass C90-C. C90-A Electronic Compass Fluxgate Compass Sensor Low Cost C90-B Hard/soft Magnetic Calibration Algorithm Sealed Electronic Compass Integrated with 3 Axis Fluxgate Sensor C90-C Full Attitude Digital Output 3D Electronic Compass single circuit board for Thermal Imaging Binocular

Key PointsProduct: Wireless Tilt Sensor for Airfoil Deflection MeasurementFeatures: Improved biaxial error model for active airfoil deflection Wireless real-time display (data, curves, 3D models) High accuracy (<0.05°) and fast acquisition (>10 Hz) Automated calibration for unparallel surfacesAdvantages: High precision and efficiency for wing deflection testing Simplified installation and operation with wireless setup Ideal for large aircraft assembly lines, enhancing workflow and reducing labor Based on the underlying measurement principle of the tilt sensor, considering the sensor system error, operation and installation error, and referring to the existing spatial Angle error analysis model, we improve the spatial Angle biaxis measurement error model suitable for the situation of moving airfoil deflection around the horizontal axis, and improve the calibration method according to the working condition. By using wireless transmission as a communication method, a complete set of moving wing deflection test system is built, which can display the Angle information of the moving wing in real time by visual means such as data, curves and three-dimensional models. The deflection Angle measurement accuracy is less than 0.05°, and the acquisition frequency is higher than 10 Hz, which can meet the actual measurement requirements. Modern aircraft manufacturing mainly adopts modular assembly technology, the whole aircraft components in the assembly line to complete modular manufacturing and equipment installation test, and finally complete the docking of large parts on the final assembly pulsating production line to form the whole machine. For large aircraft, there are many types and quantities of movable airfoil, high profile accuracy requirements, many control and coordination links involved, large manufacturing and debugging workload, and complex installation and debugging processes. The detection of deflection Angle is an important part of modular wing assembly test. There are many types and complex structure of the rudder surface of a certain key model, and the tilt sensor equipment installation of the traditional method of wing deflection Angle detection is cumbersome, the types of mechanical fixtures required are large, and the operation of workers is time-consuming and laborious. With the growing demand for various types of high-performance aircraft, the manufacturing tasks of aircraft manufacturers are increasing, and the production line needs an accurate, fast and real-time movable wing automatic inspection operating system that can reflect the production process in real time to improve the production line efficiency and ultimately increase the aircraft output.At present, the commonly used methods to detect the deflection Angle of the active airfoil space include inertial measurement, laser tracker detection, visual detection, coordinate detection, multi-theodolite detection, linear displacement or angular displacement sensor indirect detection, mechanical protractor, etc. The methods are various, but all have certain shortcomings. Therefore, many studies have combined the above methods to improve the accuracy and applicability of measurement. The inertial measurement method based on tilt sensor is relatively portable, the measurement accuracy and efficiency can meet the actual demand, so we finally choose this method to test the deflection of moving airfoil. System design and implementation (1) A biaxial measurement error model is proposed for the scenario of the active airfoil deflecting around the horizontal axis. Considering the actual working conditions of the active airfoil deflecting, a new error variable is introduced to improve the calibration algorithm, so that the tilt sensor calibration algorithm can adapt to the special working conditions of the unparallel mounting surface. The calibrated sensor Angle output accuracy is improved, and the error is within the allowable range, which can meet the high precision testing requirements of the wing moving surface Angle.(2) Complete the design and implementation of a large aircraft wing active wing deflection test system based on wireless communication protocol, and the field verification that it can achieve the mission objectives. Compared with the previous system, the hardware installation of the system does not need to connect wired communication cables, and the operation is simple. The calibration work can be automatically completed through software control, and the accuracy and real-time performance of data transmission under the wireless network can also be guaranteed, which can significantly improve the work efficiency of field active wing deflection test.(3) Only installation errors were considered in the analysis of the measurement model of spatial Angle. In fact, there is coupling between all kinds of errors. In the subsequent research, we can try to identify all kinds of errors of the system as a whole to improve the measurement accuracy of the calibration model. Summary   Micro-Magic's two very popular wireless tilt sensors, T7000-I-Modbus, accuracy can reach 0.001°, resolution 0.0005°, T7000-K-Modbus accuracy moderate 0.1°, resolution 0.01°, you can choose according to your own needs, If you are interested in our wireless tilt sensors, please feel free to contact us.   T7000-I Whatever you needs, CARESTONE is at your side.   T7000-K Whatever you needs, CARESTONE is at your side.  

  Key PointsProduct: Tilt Sensor (Inclinometer)Features:• Measures angle and slope• Single-axis, two-axis, or wireless options• MEMS or gyroscope-based• Low power, battery-operated options• Built-in protective functions Advantages:• High accuracy (up to 0.1°)• Compact, lightweight, energy-efficient• Anti-vibration, waterproof, dustproof• Wireless models reduce wiring and interference• Supports real-time remote monitoring Applications:• Robotics, marine, industrial vehicles, aerospace• Safety systems, mobile phones, ski slopes   Tilt sensors are also known as inclinometers. They are a type of position sensor used to measure the Angle or slope of an object.Inclinometers are one of the most common types of position sensors and are widely used in many industries.   1.Tilt sensor application Tilt sensor Angle and slope. So anything that works on Angle will use a inclinometer sensor or a rotary position sensor.Some sample applications include:Robotics: Tilt sensors are used to sense the Angle of the robot arm to ensure that the arm movement is in a precise position.Marine applications: inclinometer sensors are used in a variety of Marine applications, especially boom Angle sensing.Industrial vehicles: In industrial vehicles, tilt sensors are used to monitor tip protection and for a variety of applications in cranes and construction vehicles.Aerospace: tilt sensors are used for aircraft orientation and applications on the red arrow.Industrial applications: Platform leveling is a popular application in the industrial sector that uses inclinometer sensors.Safety: Tilt sensor Monitors security camera Angle sensing and mobile safety systems.Mobile phones: Mobile phones are integrated with a very small tilt sensor that changes the orientation of the screen depending on how the phone is held.Measure ski slope: for safety reasons. 2.How the tilt sensor works There are different types of inclinometer sensors, and they work slightly differently.A simple tilt sensor works by using a metal ball that connects two pins and moves within the sensor. When the sensor is tilted, the ball moves position, which connects the circuit that turns the sensor on or off.More sophisticated inclinometer sensors use an internal gyroscope to measure the direction of the gravitational pull to determine the orientation of the device. Micro-Magic's tilt sensor is actually the use of MEMS plus meter in the static state can measure the principle of angular velocity. At present, there are conventional (single-axis), dynamic (two-axis), wireless inclinometer sensors, wired and wireless have their own advantages and disadvantages. We can choose the model according to the application scenario and accuracy requirements. The single-axis T70-A, with an accuracy of 0.2°, is a very popular one with a wide range of applications. Is a very good choice, wireless T7000-K, accuracy up to 0. 1°, is an ultra-low power, small volume, high-performance wireless inclinometer sensors, for industrial applications users do not need power supply or real-time dynamic measurement of object attitude Angle needs. Using lithium battery power supply, based on the Internet of Things technology Bluetooth and ZigBee(optional) wireless transmission technology, all internal circuits are optimized design, using industrial MCU, three-proof PCB board, imported cables, wide temperature metal shell and other measures to improve the industrial level of the product. Good long-term stability, zero drift small, can automatically enter low-power sleep mode, get rid of the dependence on the use environment. The product has compact structure, precise design, temperature and linearity compensation function, and integrates short-circuit, instantaneous high voltage, polarity, surge and other comprehensive protection functions, easy to use. Wireless digital signal transmission mode eliminates the tedious wiring and noise interference caused by long cable transmission; Industrial design has extremely high measurement accuracy and anti-interference ability. Wireless sensor nodes can form a huge wireless network, supporting thousands of measurement points to monitor the tilt at the same time, and support professional computer software. Without on-site investigation, it can measure and record the status of the tested object in real time. The safety monitoring system is suitable for remote real-time monitoring and analysis of industrial sites, dilapidated buildings, ancient buildings, civil engineering, various tower incline deformation and other needs. 3.Tilt sensor characteristics and specifications The tilt sensor has the following characteristics;High reliabilityHigh accuracyEasy to operateNot using much electricityLow costSmall size, light weight, low power consumptionAnti-vibration, anti-impact, waterproof and dustproofHigh stability, low noise, strong anti-interference ability   Different types of inclinometer sensors have different specifications to suit different applications. When choosing a tilt sensor, it is important to consider the following factors;Sensitivity Some tilt sensors are more sensitive than others, depending on how the increment you need to measure affects the sensitivity of the desired sensor.Axis number: The number of axes affects the Angle and direction that the sensor can measure.Resolution: The resolution affects the minimum tilt that the sensor needs to detect.Measuring range: What is the measuring Angle in the application? This will affect the type of sensor selected.Accuracy: Different applications may require different degrees of accuracy, so it is important to choose a inclinometer sensors that reflects the requirements.Noise tolerance: Our inclinometer sensors provide standard noise tolerance.Certification: requires that we provide inclinometer sensors for intrinsically safe environments as well as underwater applications. T70-A T70-A industrial grade Inclinometer 2 -axis Acc TLL interface for Aerial work vehicle Gimbal leveling Medical equipment   T7000-K High-performance tilt sensor based on Bluetooth and Zigbee (optional) wireless transmission technology  

Key PointsProduct: Tilt Angle Monitoring SensorsFeatures: Monitors tilt angles to prevent accidents and ensure equipment operation Wireless transmission via IoT (Bluetooth, ZigBee) Durable, industrial-grade design (IP67, low power, zero drift) Real-time voltage output (0-10V，0.5-4.5V, 0~5V options) Optimized for harsh conditions Applications: Marine: Monitors ship stability Construction: Measures machine tilt Infrastructure: Tracks building and bridge tilt Tree Monitoring: Detects tree movement post-storm Gate Monitoring: Ensures proper gate operation Advantages: High precision (0.01°) Reliable in extreme conditions Suitable for multiple industries   1. Why do people monitor tilt angles? The world is constantly changing, and the tendencies of different objects and machines can provide insight into worrying trends and potential future problems. There are many reasons why people need to monitor the Angle or degree of inclination. Avoid accidents and injuries One reason is that it can help prevent injuries and avoid accidents. When people work on the slope, they need to pay attention to the Angle of the slope to ensure that they do not slip. If the Angle is too steep, it can cause an avalanche, which is very dangerous. Ensure the normal operation of the device Another reason to monitor the tilt Angle, or tilt, is to make sure the equipment is working properly. For example, if a machine is not level, it may not work properly. This can be dangerous for the person using the device and the people around it. 2. Where can the tilt sensor be used? Tilt sensors can be used in many applications, such as the Marine industry, construction industry, infrastructure monitoring, etc. Marine industry Tilt sensors can be used on ships to measure ship roll and pitch. This information can be used to improve the stability of the ship and avoid capsizing. Construction industry In many construction machines, such as excavators and bulldozers, tilt sensors can be used to measure the Angle of the machine blade or bucket. This information can be used to automatically adjust the position of the blade or bucket, or to provide feedback to the operator. Infrastructure monitoring Tilt sensors can be used to monitor the status of infrastructure such as Bridges and buildings and alert authorities to potential hazards, such as leaning towers. By continuously monitoring the tilt of the structure, the sensors can detect even the smallest changes that could indicate a problem. In the event of a potential accident, sensors can provide critical information that can be used to evacuate people and take other safety measures. Tree bend monitoring Some trees may fall after storms, typhoons or other natural disasters. Tilt sensors can be installed at a certain height on these trees to monitor their x, y, and z values in real time. This can provide insights into tree tilt and movement and help make timely, effective decisions to protect trees and people. Gate monitoring In car parking lots and parking garages, the normal operation of road gates is crucial to the normal toll collection. The tilt sensor can be installed in the guardrail housing, especially suitable for the guardrail Angle measurement and movement detection, to determine whether the guardrail is dropped, bent or broken, if there is a trigger alarm, so that maintenance personnel can take measures in time. Ensure regular charges. 3. Summary Micro-Magic's T7000-K precision up to 0.01°, the use of advanced Internet of Things technology Bluetooth and ZigBee(optional) wireless transmission technology, all internal circuits are optimized design, using industrial MCU, three-proof PCB board, imported cables, wide temperature metal shell and other measures, Improve the industrial level of products. Good long-term stability, zero drift small, can automatically enter low-power sleep mode, get rid of the dependence on the use of the environment, equipped with IP67-rated housing, so that it can withstand harsh conditions and still work normally. The optimized internal design of multi-layer structure, sealing ring, and three anti-coating further enhances the waterproof and dustproof capability. The T7000-I voltage uniaxial tilt sensor is an analog voltage uniaxial tilt sensor. The user only needs to collect the sensor voltage value to calculate the tilt Angle of the current object. The built-in (MEMS) solid pendulum measures changes in the static gravity field, converts them into changes in inclination, and outputs them via voltage (0~10V, 0.5~4.5V, 0~5V optional). The product adopts the non-contact measurement principle and can output the current attitude and inclination Angle in real time. If you would like more technical data, please feel free to contact us.

  Key PointsProduct: Attitude and Heading Reference System (AHRS)Features:• Provides real-time attitude information (pitch, roll, yaw)• Uses gyroscopes, accelerometers, and magnetometers for sensor fusion• High precision and low latency for dynamic environments• Uses algorithms like Kalman filter and complementary filter for data fusion• Compact and lightweight, ideal for aerospace, marine, and autonomous applications Applications:• Aerospace: Monitors flight status and stability in aircraft and UAVs• Autonomous Vehicles: Ensures stable navigation in self-driving cars• Marine: Tracks attitude for underwater vehicles and submarines• AR/VR: Captures user head movements for immersive experiences Advantages:• High precision and reliability in real-time navigation• Reduces dependency on manual monitoring and traditional methods• Easily integrates with other navigation systems like GPS• Works in various environmental conditions (extreme temperatures, vibrations, etc.)• Low power consumption and efficient for extended use in dynamic settings   The Attitude and Heading Reference System (AHRS) is a device widely used in aerospace, unmanned vehicles, marine exploration, and other precision navigation fields. Its primary function is to provide real-time attitude information (such as pitch, roll, and yaw) by measuring the acceleration and angular velocity of the aircraft or spacecraft, enabling precise navigation and control.   1. Working Principle of AHRS The core components of AHRS typically include gyroscopes, accelerometers, and magnetometers. These sensors provide real-time data to sense the motion state of the vehicle. The gyroscope provides angular velocity information, the accelerometer measures acceleration, and the magnetometer helps calibrate the heading angle. In practical applications, AHRS needs to use sensor fusion algorithms to combine data from different sensors and provide accurate attitude estimation. Common algorithms include Kalman Filtering and Complementary Filtering. These algorithms help correct sensor errors and provide reliable heading and attitude information. 2. Attitude Estimation and Mathematical Model   One of the core tasks of AHRS is attitude estimation. Attitude refers to the orientation of an object relative to the Earth's reference coordinate system, usually represented by three angles: pitch, roll, and yaw. There is a close mathematical relationship between these angles and the output signals from inertial sensors. Let the accelerometer and angular velocity sensor outputs be represented by , and ,respectively. The estimation of attitude angles can be computed using the following formulas: (1)Relationship between Angular Velocity and Attitude AnglesThe change in attitude angles can be calculated from the angular velocity. The relationship between angular velocity and the rate of change of attitude angles is given by where represents the yaw (heading angle), pitch angle, and roll angle, and is the Jacobian matrix describing the mapping from angular velocity to attitude angles.   (2)Relationship between Acceleration and Attitude Angles For the acceleration data from the accelerometer ,the following equation combines the acceleration data with attitude angles:,whereis the rotation matrix that describes the rotation between the body frame and the world frame. This matrix allows the conversion of acceleration data from the world coordinate system to the body coordinate system. (3)Complementary Filter and Kalman Filter    In practice, AHRS systems use complementary filters or Kalman filters to fuse data from different sensors. The basic idea of complementary filtering is to leverage the low-frequency data from the accelerometer and the high-frequency data from the gyroscope to smooth the attitude estimation process and reduce noise. The formula for the complementary filter is: 1.Where   is the current estimated attitude, is the angular velocity from the gyroscope,  is the attitude estimated from the accelerometer,  is the fusion coefficient, and  is the time interval. The Kalman filter, on the other hand, uses prediction and update steps to optimize attitude estimation, providing more accurate results in dynamic environments. 3. Applications of AHRS With the continuous development of technology, the application fields of AHRS have expanded. Below are several typical applications: Aerospace: In aircraft, spacecraft, and unmanned aerial vehicles (UAVs), AHRS is one of the fundamental attitude navigation systems, used to monitor flight status in real-time and ensure the stability of the vehicle. Autonomous Vehicles: In autonomous cars, AHRS provides real-time attitude information to help the vehicle maintain stable motion, especially in complex environments where positioning and control are crucial. Marine Exploration: Submarines and underwater robots rely on AHRS to obtain attitude data for underwater navigation, ensuring proper heading and positioning. Augmented Reality and Virtual Reality: In AR/VR devices, AHRS is used to capture head movements of the user, enabling immersive experiences. 4. Future Development Trends With advancements in microelectronics, sensor technologies, and data processing capabilities, the performance and application prospects of AHRS systems continue to improve. In the future, AHRS is expected to make significant progress in the following areas: High-Precision Sensors: The next generation of high-precision, low-power sensors will further enhance the performance of AHRS, especially in harsh environments. Intelligent Algorithms: With the development of artificial intelligence, AHRS will implement more intelligent data fusion and attitude estimation algorithms, offering more precise navigation support. Multi-Sensor Fusion: In the future, AHRS will increasingly integrate with GPS, vision sensors, and other navigation technologies, forming a more comprehensive and reliable navigation system. 5. Conclusion   As a crucial component of navigation and positioning technologies, AHRS plays an increasingly important role in various fields. With the continuous advancement of technology, AHRS will provide stronger support for precise navigation, driving the development of automation and intelligence. By gaining a deeper understanding of AHRS’s working principles and its application prospects, we can better grasp the opportunities and challenges brought by this technology. A500 3 axis accelerometer+3 axis magnetometer+3 axis Gyro Digital Output RS232/485/CAN/TTL optional A5500 Imu Ahrs Ins Gnss Inertial Sensor for Agri Robot Competitive Price A5000 Tactical Grade Integrated Mems Accelerometer Gyroscope Magnetometer Altitude Heading Sensor AHRS for UAV drone