Applications

Key Points    **Product**: Micro-Magic Inc’s MEMS IMU U5000, a tactical-grade, high precision, 9-axis IMU for drones.**Features**:  44.8×38.6×21.5mm size, 60g weight.  9-axis with a three-axis magnetometer.  Gyroscope: ±400º/s dynamic range, 0.5º/h bias instability, 0.08º/√h angular random walk.  Accelerometer: ±30g dynamic range, 0.01mg bias stability.  Power: 1.5W, energy-efficient for drones.**Advantages**: Suitable for drones, lightweight, cost-effective, mass-producible.**Magnetometer**: Helps with heading/yaw correction.   As one of the core components of drones, IMU plays an irreplaceable role. Its high precision, fast response and freedom from external interference enable drones to maintain stable and precise flight and accurate navigation and positioning in complex environments, and can also perform fault diagnosis for drones. Micro-Magic Inc’s MEMS IMU can achieve high performance while being small in size and light in weight, making it very suitable for drones.We have a tactical-grade IMU U5000 which is low-cost and has an advantage in price. It is a 9-axis IMU with an added three-axis magnetometer. It is only 44.8×38.6×21.5mm in size and weighs 60g. Compared with other IMUs, it is more suitable for drones. The built-in accelerometer of the IMU cannot be used to detect absolute heading (yaw). The magnetometer in this IMU measures the magnetic field strength in three dimensions, which can help determine the heading of the object as well as roll and pitch, and correct the integrated error of the yaw gyroscope in the sensor fusion algorithm.The dynamic measurement range of the built-in gyroscope is ±400º/s, the bias instability is 0.5 º/h, and the angular random walk is 0.08º/√h. The dynamic measurement range of the accelerometer is ±30g, the bias stability is 0.01mg (Allen variance).Considering the flight time requirements of drones, this IMU has a power of only 2W, which can extend the flight time of drones.This IMU has a short production cycle and can be mass-produced, which is particularly suitable for users with large demands and limited budgets.If you are interested in this and want to know more, please follow me and send me a message, I will reply immediately. I will update the relevant content later. U5000 Industrial Grade Temperature Compsensated Full Calibrated Strapdown 6Dof With Kalman Filter Algorithm U7000 Rs232/485 Gyroscope Imu For Radar/infrared antenna stabilization platform UF100A Middle Precision And Small Size IMU Fiber Optic Inertial Group    

Key Points Product: Micro-Magic Inc’s MEMS IMU U5000, a tactical-grade, low-cost, 9-axis IMU for drones. Features: Size: 44.8×38.6×21.5mm, Weight: ≤60g 9-axis with three-axis magnetometer and barometer Gyroscope: ±400º/s dynamic range, bias instability <0.5º/h, angular velocity random walk <0.08º/√h Accelerometer: ±30g dynamic range, bias repeatability 0.01mg Power: 2W, energy-efficient for extended flight Advantages: Ideal for drones, lightweight, cost-effective, and customizable for OEM, enhancing stability and performance with magnetometer aiding in heading correction. The key to achieving autonomous navigation, stable control and precise flight of drones is closely related to IMU, which is one of the core technologies of drone systems. At present, there are also research teams that have developed IMU-centric data-driven diagnostic methods to perform fault diagnosis on drones without the need for additional sensors. Choosing the right IMU can make flight more stable and safer.Micro-Magic Incs MEMS IMU U5000 and U7000 (can be customized for OEM) can be used in drones. Using MEMS technology, they are small in size, superior in performance, light in weight, low in power consumption, and cost-effective, and are very popular among users.Drones have strict requirements on the size and weight of IMUs. The U5000 has a size of (44.8×38.6×21.5mm(with shell)) and a weight of ≤60g (with shell). Flight control of drones is one of their most basic functions. MEMS IMU helps drones maintain a stable attitude by providing real-time acceleration and angular velocity data. The gyroscope measurement range of U5000 and U7000 is ±400deg/s, bias instability <0.5deg/hr, angular velocity random walk <0.08°/√h, accelerometer bias repeatability 0.01mg. At the same time, it has the characteristics of low power consumption, which prolongs the flight time of drones.It can also combine data from other sensors (such as GPS, magnetometer, etc.) to calculate the precise location and attitude information of the drone for navigation and positioning. When the drone is taking aerial photos, it can maintain extremely high stability to ensure the clarity and stability of the images and videos taken. At the same time, it can also be used as part of the drone’s fault safety system to detect abnormal movements or attitude changes and trigger automatic recovery procedures or emergency landing procedures to protect the safety of the drone and the surrounding environment.In the design and application of drones, high-performance IMUs are able to provide stable and accurate data under various environmental conditions, such as temperature changes, vibrations, and rapid movements, and perform precise tasks such as aerial photography, logistics transportation, and agricultural monitoring.MEMS IMU has many applications in the field of drones. They not only improve the performance and stability of drones, but also expand the scope of application of drones. If you are interested in this and want to know more, please follow me and send me a message. I will reply immediately. I will update the relevant content later. U5000 Industrial Grade Temperature Compsensated Full Calibrated Strapdown 6Dof With Kalman Filter Algorithm   U7000 Rs232/485 Gyroscope Imu For Radar/infrared antenna stabilization platform

Key Points Product: Micro-Magic Inc’s MEMS IMU UF300A (Navigation-grade) vs UF100A (Tactical-grade). Navigation-grade UF300A Features: Size: Compact for various applications Gyroscope: Bias repeatability <0.05°/hr, bandwidth 100Hz Accelerometer: High precision for navigation tasks Power: Efficient for long-duration use Tactical-grade UF100A Features: Size: Similar compact design Gyroscope: Bias repeatability <0.2°/hr, bandwidth 300Hz Accelerometer: Robust for tactical missions Power: Optimized for demanding environments Advantages: UF300A excels in precision for navigation; UF100A is tailored for high-precision applications like drone navigation and stabilization, offering flexibility and reliability in critical tasks. Introduce Navigation-grade IMU and Tactical-grade IMU are different levels of inertial measurement units (IMU). They have significant differences in accuracy, performance and application scenarios. Navigation-level and tactical-level IMU will be introduced below. Navigation grade MEMS IMU First of all, navigation-grade IMU is mainly used for general navigation and positioning tasks, and its performance requirements are relatively low. It usually has high accuracy and reliability and can meet the needs of most navigation applications. Through internal sensors such as accelerometers and gyroscopes, the navigation-grade IMU can accurately measure key information such as the acceleration, angular velocity, and direction of objects. After processing, this information can be used to achieve precise positioning and navigation functions, thereby improving driving safety and stability. Tactical Grade MEMS IMU Tactical-grade IMU have some unique core features. For example, they are able to operate gyroscopes with extremely low bias stability, meaning that bias errors become more stable over time. This stability is critical for high-precision applications such as drone navigation. And for higher-precision applications, such as drone navigation, antenna and weapon platform stabilization, tactical-grade IMU are required. Gyroscopes are known to operate with extremely low bias stability, meaning their bias errors remain relatively stable over time. This feature allows tactical-grade IMU to maintain excellent performance in long-term, high-precision applications. In addition, tactical-grade IMU are usually equipped with high-quality MEMS accelerometers and gyroscopes to provide more accurate data output.   It can be seen that navigation-grade IMU and tactical-grade IMU have different emphasis on accuracy, performance and application scenarios. When selecting an IMU, the most appropriate level needs to be determined based on specific application requirements. The following will briefly describe the differences between navigation-grade MEMS IMU and tactical-grade MEMS IMU, and introduce two IMU from the domestic inertial navigation company Micro-Magic Inc. Navigation grade MEMS IMU VS Tactical grade MEMS IMU There are significant differences in performance and application between navigation-grade IMU and tactical-grade IMU. First, navigation-grade IMU are usually used in some scenarios with relatively high accuracy requirements, and their performance and accuracy are higher than tactical-grade IMU. The performance and accuracy of tactical-grade IMUs are far inferior to those of navigation-grade IMU, so tactical-grade IMUs are the first choice for demanding applications such as drone navigation. These IMU operate gyroscopes with extremely low bias stability, which means that the bias error becomes more stable over time. This feature is essential for critical missions and high-precision applications such as drone navigation, antenna and weapon platform stabilization. Micro-Magic Inc is an inertial navigation company that independently develops MEMS IMU. The MEMS IMU it develops are mainly divided into navigation level and tactical level. The following are the company’s UF300A(navigation level) and UF100A (tactical level). Level) built-in MEMS gyroscope specification comparison:   UF100A UF300A Bias repeatability <0.2deg/hr <0.05deg/hr Range 300 300 Bias stability (10s 1σ) <0.2deg/hr <0.05deg/hr Bandwidth (-3dB) 300Hz 100Hz Threshold <0.1°/√h <0.005°/ √h It can be seen from the above table that the accuracy of the built-in gyroscope of the navigation-grade MEMS IMU is much higher than that of the tactical-grade one, especially the bias repeatability of the navigation-grade one is 0.05, and the tactical-grade one is 0.2. The accuracy is much higher. NF100A has a larger range than NF300A. Summarize Navigation-grade IMU and tactical-grade IMU are different in accuracy, stability and applicable scenarios. When selecting, the most appropriate IMU type needs to be determined based on specific application requirements. For more professional information, please consult our relevant personnel. UF100A Middle Precision And Small Size IMU Fiber Optic Inertial Group   UF300 High-precision Miniaturized Inertial Measurement Unit Fiber Optic Inertial Measurement Unit  

Key Points Product: Ground Positioning Method with IMU and Fixed Camera Key Features: Components: Inertial Measurement Unit (IMU) and fixed camera, securely mounted for stable positioning. Function: Combines high-precision attitude measurement from IMU with visual positioning from the camera for accurate ground positioning. Applications: Suitable for drones, robotics, and autonomous vehicles. Data Fusion: Integrates IMU data with camera imagery to determine precise geographical coordinates. Conclusion: This method enhances positioning accuracy and efficiency while simplifying calibration, with potential for broad applications in various technological fields. Introduce A ground positioning method in which an inertial measurement unit (IMU) and a camera are fixedly installed. It combines the high-precision attitude measurement of the IMU and the visual positioning capabilities of the camera to achieve efficient and accurate ground positioning. Here are the detailed steps of the method: First, install the IMU and the camera firmly to ensure that the relative position between them remains unchanged. This installation method eliminates the tedious steps of calibrating the installation relationship between the camera and the IMU in the traditional method, and simplifies the operation process. Next, the IMU is used to measure the acceleration and angular velocity of the carrier in the inertial reference frame. The IMU contains an acceleration sensor and a gyroscope, which can sense the motion status of the carrier in real time. The acceleration sensor is responsible for detecting the current acceleration rate, while the gyroscope detects changes in the direction, roll angle and tilt attitude of the carrier. These data provide key information for subsequent attitude calculation and positioning. Then, based on the data measured by the IMU, the attitude information of the carrier in the navigation coordinate system is calculated through integral operation and attitude solution algorithm. This includes the yaw angle, pitch angle, roll angle, etc. of the carrier. Due to the high update frequency of the IMU, the operating frequency can reach more than 100Hz, so it can provide high-precision attitude data in real time. At the same time, the camera captures ground feature points or landmark information and generates image data. These image data contain rich spatial information and can be used for fusion processing with IMU data. Next, the attitude information provided by the IMU is fused with the image data of the camera. By matching the feature points in the image with known points in the geographical coordinate system, combined with the attitude data of the IMU, the precise position of the camera in the geographical coordinate system can be calculated. Finally, the projection matrix is used to intersect the normal-line intersection to obtain the spatial position of the target. This method combines the attitude data of the IMU and the image data of the camera to achieve an accurate estimation of the target spatial position by calculating the projection matrix and intersection point. Through this method, high-precision and high-efficiency ground positioning can be achieved. The fixed installation of the IMU and the camera simplifies the operation process and reduces calibration errors. At the same time, the combination of the IMU’s high update frequency and the camera’s visual positioning capability improves positioning accuracy and real-time performance. This method has broad application prospects in fields such as drones, robots, and autonomous driving. It should be noted that although this method has many advantages, it may still be affected by some factors in practical applications, such as environmental noise, dynamic interference, etc. Therefore, in practical applications, parameter adjustment and optimization need to be carried out according to specific conditions to improve the stability and reliability of positioning. Summarize The above article describes the ground positioning method when the IMU and the camera are fixedly installed. It briefly describes the IMU’s high-precision attitude measurement and the camera’s visual positioning capabilities, and can achieve efficient and accurate ground positioning. The MEMS IMU independently developed by Micro-Magic Inc has relatively high accuracy, such as U3000 and U7000, which are more accurate and are navigation-grade products. It can accurately locate and orient. If you want to know more about IMU, please contact our professional technicians as soon as possible. U7000 Rs232/485 Gyroscope Imu For - Radar/infrared antenna stabilization platform   U3000 IMU MEMS Sensor IMU3000 Accuracy 1 Digital Output RS232 RS485 TTL Optional Modbus  

Key Points Product: GNSS-aided MEMS Inertial Navigation System (INS) Key Features: Components: Equipped with MEMS gyroscopes and accelerometers for accurate inertial measurements, with GNSS support for enhanced navigation. Function: Combines short-term INS precision with long-term GNSS stability, delivering continuous navigation data. Applications: Suited for tactical operations, drones, robotics, and industrial automation. Data Fusion: Merges INS data with GNSS corrections to reduce drift and improve positioning accuracy. Conclusion: Delivers high precision and reliability, ideal for navigation tasks across diverse industries. In the noise reduction process of IMU (Inertial Measurement Unit), wavelet denoising is an effective method. The basic principle of wavelet denoising is to use the multi-resolution time-frequency localization characteristics of wavelets to decompose the components of different frequencies in the signal into different subspaces, and then process the wavelet coefficients in these subspaces to remove noise. Specifically, the process of wavelet denoising can be divided into the following three steps: 1.Perform wavelet transformation on the noisy IMU signal and decompose it into different wavelet subspaces. 2.Threshold the coefficients in these wavelet subspaces, that is, coefficients below a certain threshold are regarded as noise and set to zero, while coefficients above the threshold are retained, and these coefficients usually contain useful signal information. 3.Perform inverse transformation on the processed wavelet coefficients to obtain the denoised signal. This method can effectively remove the noise in the IMU signal and improve the quality and accuracy of the signal. At the same time, because the wavelet transform has good time-frequency characteristics, it can better retain the useful information in the signal and avoid excessive information loss during the denoising process. Please note that the specific threshold selection and processing methods may vary according to specific signal characteristics and noise conditions, and therefore need to be adjusted and optimized according to specific circumstances in actual applications. The IMU data denoising method based on wavelet decomposition is an effective signal processing technology used to remove noise from IMU (Inertial Measurement Unit) data. IMU data often contains high-frequency noise and low-frequency drift, which can affect the accuracy and performance of the IMU. The noise reduction method based on wavelet decomposition can effectively separate and remove these noises and drifts, thereby improving the accuracy and reliability of IMU data. Wavelet decomposition is a multi-scale analysis technique that can decompose signals into wavelet components of different frequencies and scales. By wavelet decomposing the IMU data, high-frequency noise and low-frequency drift can be separated and processed differently. The IMU data denoising method based on wavelet decomposition usually includes the following steps: 1.Perform wavelet decomposition on the IMU data and decompose it into wavelet components of different frequencies and scales. 2.According to the characteristics of the wavelet components, select an appropriate threshold or wavelet coefficient processing method to suppress or remove high-frequency noise. 3.Model and compensate for low-frequency drift to reduce its impact on IMU data. 4.Reconstruct the processed wavelet components to obtain denoised IMU data.   The IMU data denoising method based on wavelet decomposition has the following advantages: 1.Able to effectively separate and remove high-frequency noise and low-frequency drift, improving the accuracy and reliability of IMU data. 2.Have good time-frequency analysis capabilities and be able to process the time and frequency information of signals at the same time. 3.Suitable for different types of IMU data and different application scenarios, with strong versatility and flexibility. Summarize In short, the IMU data denoising method based on wavelet decomposition is an effective signal processing technology that can improve the accuracy and reliability of IMU data and provide more accurate and reliable data for inertial navigation, attitude estimation, motion tracking and other fields. support. The IMU independently developed by Micro-Magic Inc uses some relatively rigorous denoising methods to better demonstrate to consumers higher-precision and low-cost MEMS IMUs, such as U5000 and U3500 as navigation series MEMS IMUs. Technicians conducted various experiments to denoise the IMU data to better meet consumers’ accurate measurement of the motion state of objects. If you want to know more about IMU, please contact our relevant personnel. U3500 IMU MEMS Sensor IMU3500 CAN Output   U5000 Whatever you needs, CARESTONE is at your side.  

Key Points Product: IMU for Pipeline Inspection Key Features: Components: Equipped with MEMS gyroscopes and accelerometers for measuring angular velocity and acceleration. Function: Monitors pipeline conditions by detecting bends, diameter variations, and cleanliness through precise measurements of motion and orientation. Applications: Used in pipeline inspection, including strain identification, diameter measurement, and cleaning processes. Data Processing: Collects and processes data for accurate assessment of pipeline health, curvature, and strain. Conclusion: Provides critical insights for pipeline maintenance, improving efficiency and reliability in inspection and maintenance operations. 1.IMU measurement principle IMU (Inertial Measurement Unit) is a device that can measure the angular velocity and acceleration of an object in three-dimensional space. Its core components usually include a three-axis gyroscope and a three-axis accelerometer. Gyroscopes are used to measure the angular velocity of an object about three orthogonal axes, while accelerometers are used to measure the acceleration of an object along three orthogonal axes. By integrating these measurements, the velocity, displacement and attitude information of the object can be obtained. 2.Pipe bending strain identification In pipeline inspection, IMU can be used to identify the bending strain of the pipeline. When an IMU is installed on a pig or other mobile device and moves within a pipeline, it can sense changes in acceleration and angular velocity caused by pipeline bending. By analyzing this data, the degree and location of pipe bends can be identified. 3.Diameter measurement and pipe cleaning process The diameter measuring and cleaning process is an important part of pipeline maintenance. In this process, a caliper pig equipped with an IMU is used to move along the pipeline, measure the inner diameter of the pipeline, and record the shape and size of the pipeline. This data can be used to assess the health of pipelines and predict possible maintenance needs. 4.Steel brush cleaning process The steel brush pigging process is used to remove dirt and sediment from the inner walls of pipelines. In this process, a pig with a steel brush and an IMU moves along the pipeline, cleaning the inner wall of the pipeline through brushing and scouring. The IMU can record the geometric information and cleanliness of the pipeline during this process. 5.IMU detection process The IMU inspection process is a key step in using IMU for data collection and measurement during pipeline maintenance. The IMU is installed on a pig or similar equipment and moves inside the pipeline while recording acceleration, angular velocity and other parameters. This data can be used to analyze the health of the pipeline, identify potential problems, and provide a basis for subsequent maintenance and management. 6.Data acquisition and post-processing After completing the IMU detection process, the collected data need to be collected and post-processed. Data acquisition involves transferring raw data from the IMU device to a computer or other data processing device. Post-processing involves cleaning, calibrating, analyzing and visualizing the data. Through post-processing, useful information can be extracted from the original data, such as the shape, size, bending degree, etc. of the pipe. 7.Speed and attitude measurement IMU can calculate the speed and attitude of an object by measuring acceleration and angular velocity. In pipeline inspection, measurement of speed and attitude is critical to assess the health of the pipeline and identify potential problems. By monitoring the speed and attitude changes of the pig in the pipeline, the shape, bending degree and possible obstacles of the pipeline can be inferred. 8.Pipe Curvature and Strain Assessment Using the data measured by the IMU, the curvature and strain of the pipeline can be evaluated. By analyzing acceleration and angular velocity data, the radius of curvature and bending angle of the pipe at different locations can be calculated. At the same time, combined with the material properties and loading conditions of the pipe, the strain level and stress distribution of the pipe at the bend can also be evaluated. This information is important for predicting the life of pipelines, assessing safety, and developing maintenance plans. Summarize To sum up, IMU plays an important role in pipeline inspection. By measuring parameters such as acceleration and angular velocity, comprehensive assessment and maintenance of pipeline health can be achieved. With the continuous advancement of technology and the expansion of application fields, the application of IMU in pipeline inspection will become more and more extensive. The MEMS IMU independently developed by Micro-Magic Inc has relatively high accuracy, such as U5000 and U7000, which are more accurate and are navigation-grade products. If you want to know more about IMU, please contact our professional technicians as soon as possible. U7000 Industrial Grade Temperature Compsensated Full Calibrated Strapdown 6Dof With Kalman Filter Algorithm   U5000 Rs232/485 Gyroscope Imu For Radar/infrared antenna stabilization platform  

Key Points Product: Pure Inertial Navigation System (INS) Based on IMU Key Features: Components: Uses MEMS accelerometers and gyroscopes for real-time measurement of acceleration and angular velocity. Function: Integrates initial position and attitude data with IMU measurements to calculate real-time position and attitude. Applications: Ideal for indoor navigation, aerospace, autonomous systems, and robotics. Challenges: Addresses sensor errors, cumulative drift, and dynamic environment impacts with calibration and filtering methods. Conclusion: Provides precise positioning in challenging environments, with robust performance when combined with auxiliary positioning systems like GPS.   Pure inertial data (IMU) position calculation is a common positioning technology. It calculates the target object in real time by using the acceleration and angular velocity information obtained by the Inertial Measurement Unit (IMU), combined with the initial position and attitude information. s position. This article will introduce the principles, application scenarios and some related technical challenges of pure inertial navigation data position calculation. 1. Principle of position calculation based on pure inertial navigation data Pure inertial navigation data position calculation is a positioning method based on the principle of inertial measurement. IMU is a sensor that integrates an accelerometer and a gyroscope. By measuring the acceleration and angular velocity of the target object in three directions, the position and attitude information of the target object can be derived. In pure inertial navigation data position calculation, it is first necessary to obtain the initial position and attitude information of the target object. This can be achieved by introducing other sensors (such as GPS, compass, etc.) or manual calibration. The initial position and attitude information play an important role in the solution process. They provide a starting point so that the acceleration and angular velocity data measured by the IMU can be converted into the actual displacement and attitude changes of the target object. Then, based on the acceleration and angular velocity data measured by the IMU, combined with the initial position and attitude information, numerical integration or filtering algorithms can be used to calculate the position of the target object in real time. The numerical integration method obtains the speed and displacement of the target object by discretizing and integrating the acceleration and angular velocity data. The filtering algorithm uses methods such as Kalman filtering or extended Kalman filtering to filter the data measured by the IMU to obtain the position and attitude estimation of the target object. 2. Application scenarios of pure inertial navigation data position calculation Position calculation based on pure inertial navigation data is widely used in many fields. Among them, indoor navigation is one of the typical application scenarios for pure inertial navigation data position calculation. In indoor environments, GPS signals are usually unable to reach, and pure inertial navigation data position calculation can use the data measured by IMU to achieve accurate positioning of target objects indoors. This is of great significance in fields such as autonomous driving and indoor navigation robots. Pure inertial navigation data position calculation can also be used in the aerospace field. In aircraft, since the GPS signal may be interfered at high altitudes or far from the ground, pure inertial navigation data position calculation can be used as a backup positioning method. It can calculate the position and attitude of the aircraft in real time through the data measured by the IMU, and provide it to the flight control system for attitude stabilization and flight path planning. 3. Challenges of position calculation using pure inertial navigation data Position calculation based on pure inertial navigation data still faces some challenges in practical applications. First of all, the IMU sensor itself has errors and noise, which will affect positioning accuracy. In order to improve the solution accuracy, the IMU sensor needs to be calibrated and error compensated, and an appropriate filtering algorithm is used to reduce the error. Position calculation based on pure inertial navigation data is prone to cumulative errors during long-term movements. Due to the characteristics of the integration operation, even if the measurement accuracy of the IMU sensor is high, long-term integration will lead to the accumulation of positioning errors. In order to solve this problem, other positioning means (such as GPS, visual sensors, etc.) can be introduced for auxiliary positioning, or a tightly coupled inertial navigation method can be used. Position calculation based on pure inertial navigation data also needs to consider the impact of the dynamic environment. In a dynamic environment, the target object may be affected by external forces, causing deviations in the data measured by the IMU. In order to improve the robustness of the solution, the effects of dynamic environments can be compensated through methods such as motion estimation and dynamic calibration. Summarize Pure inertial data position calculation is a positioning method based on IMU measurement. By acquiring acceleration and angular velocity data, combined with initial position and attitude information, the position and attitude of the target object are calculated in real time. It has wide applications in indoor navigation, aerospace and other fields. However, pure inertial navigation data position calculation also faces challenges such as calibration error, cumulative error and dynamic environment. In order to improve the solution accuracy and robustness, appropriate calibration methods, filtering algorithms and auxiliary positioning methods need to be adopted. The MEMS IMU independently developed by Micro-Magic Inc has relatively high accuracy, such as UF300A and UF300B, which have higher accuracy and are navigation-grade products. If you want to know more about IMU, please contact our professional technicians as soon as possible.   UF300 High-precision Miniaturized Inertial Measurement Unit Fiber Optic Inertial Measurement Unit   -

Key Points Product: Tilt Angle Monitoring Sensors Features: - Monitors tilt angles for large outdoor advertisements, infrastructure, and construction. - Enables real-time data transmission via GPRS for remote monitoring. - Solar-powered for independent operation, reducing the need for external power sources. - Provides high data credibility with minimal manpower required. - Offers low cost, easy installation, and maintenance. Applications: - Outdoor Advertising: Monitors tilt of large billboards and signs to ensure optimal display angles. - Infrastructure: Tracks tilt in bridges, buildings, and dams to detect any structural issues. - Construction: Monitors the tilt of heavy machinery during operation for safety and performance evaluation. Advantages: - High precision and real-time monitoring of tilt angles. - Reduces reliance on manual inspection and traditional methods of monitoring. - Easy integration into existing monitoring systems. - Low power consumption, environmentally-friendly design with solar-powered operation. - Reliable operation in various environmental conditions, including temperature and humidity.   Inertial measurement unit (IMU) is an integrated sensor kit that combines multiple accelerometers and gyroscopes to perform three-dimensional measurements of specific force and angular velocity relative to an inertial reference frame. However, in recent years, IMU has become a general term used to describe various inertial systems, including attitude heading reference systems (AHRS) and INS. IMU itself does not provide any type of navigation solution (position, velocity, attitude) . Normally, inertial sensors can be divided into the following three performance categories:   Marine-grade and Navigation-grade inertial navigation systems :     Marine-grade inertial navigation systems are the highest level of commercial sensors used on ships, submarines, and occasionally on spacecraft. This system can provide a non assisted navigation solution with drift less than 1.8 km/day. The cost of these sensors is as high as $1 million. The performance of navigation grade inertial navigation systems is slightly lower than that of Marine-grade inertial navigation systems, and is usually used for commercial and military aircraft. Its drift is less than 1.5km/h, and its price is as high as $100000. Tactical and industrial inertial sensors: Tactical and industrial grade sensors are the most diverse among these three types of sensors, capable of addressing various performance and cost situations, and their market opportunities are enormous. This category is used for many applications that require high-performance data to be obtained at a lower cost for mass production, commonly found in automatic lawnmowers, delivery robots, drones, agricultural robots, mobile industrial robots, and autonomous ships. Consumer grade sensors: In the commercial market, these sensors are usually sold in the form of separate accelerometers or gyroscopes. Many companies have started combining multiple accelerometers and gyroscopes from different manufacturers to create independent IMU units   Choosing the appropriate inertial sensor (such as accelerometer, gyroscope, magnetometer, or combined IMU/AHRS) requires comprehensive consideration of multiple factors including application scenarios, performance parameters, environmental conditions, and costs.   1. Clarify application requirements   Dynamic range: Determine the maximum acceleration or angular velocity that the sensor needs to measure (for example, a high range gyroscope is required for high-speed maneuvering of a drone). Accuracy requirements: High precision navigation (such as autonomous driving) requires sensors with low noise and low bias. Update frequency: High frequency vibration monitoring requires a sampling rate of>1kHz, while conventional motion tracking may only require 100Hz. Power consumption limit: Wearable devices require low power consumption (such as MEMS accelerometers with ± 10mg noise), while industrial devices can be relaxed. Integration method: Do you need IMU (6-axis) or AHRS (with attitude calculation).   2. Key performance parameters   Accelerometer: Range: ±2g (inclination measurement) to ±200g (impact detection). Noise density:  < 100μg/√ Hz (high precision) vs >500 μg/√Hz (low cost). Bandwidth: It needs to cover the highest frequency of the signal (e.g. mechanical vibration may require >500Hz).   Gyroscope: Zero bias stability: < 1°/h (fiber optic gyroscope) vs 10°/h (industrial MEMS) vs 1000 °/h (consumer grade). Angle random walk (ARW): <0.1°/√h (tactical level) vs 5°/√h (consumer level). Range: ±300°/s (conventional) to ±2000 °/s (high-speed rotation).   Magnetometer: Sensitivity: 0.1μT/LSB (high-precision navigation) vs 0.5μT/LSB (universal). Orthogonal error:  <1° (reduces the influence of soft iron interference).   3. Environmental adaptability   Temperature range: Industrial grade (-40°C~85°C) vs Consumer grade (0° C~70°C). Anti vibration/impact:  For example, automotive electronics need to pass a 5g RMS vibration test. Sealing:  IP67/IP68 protection level (outdoor or humid environment).   4. Interface and power consumption   Digital interfaces: SPI/I2C (embedded systems), CAN (automotive), UART (simple communication). Power supply voltage: 3.3V (low power consumption) vs 5V (industry standard). Power consumption: < 1mA (battery device) vs unlimited (wired power supply).   Micro-Magic Inc is a high-tech company specializing in the production, manufacturing, and research and development of automotive grade and industrial grade inertial sensors. The company's inertial sensor include various series of products such as accelerometers, gyroscopes, magnetometers, inclinometers, IMUs, VRUs, AHRS, and INS+GNSS integrated navigation. Over the years, The company's products have been widely used in various application fields, including automotive, aerospace, marine vessels, industrial automation, and medical equipment. The company's products have the characteristics of high precision, low power consumption, small size, and high reliability, and are widely used in fields such as attitude control, navigation systems, motion tracking, and vibration analysis. At the same time, Micro-Magic Inc are also committed to providing customized solutions for customers to meet the specific needs of different industries U6488 MEMS High Precision Digital Output IMU Sensor U7000 High Precision MEMS IMU U300-A Digital Output High Performance MEMS IMU Sensor  

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    

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      

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