Applications

Key Points Product: Micro-Magic Inc’s MEMS GNSS/INS, including the I3500 model for mapping applications. Features: Size: Compact and lightweight for easy integration Accuracy: 2.5°/hr bias instability, 0.028°/√hr angular random walk MEMS accelerometer: ±6g range, zero bias instability <30μg GNSS integration for absolute positioning Advantages: Cost-effective, low power consumption, flexible placement, ideal for various applications like UAVs and aircraft, enhancing navigation precision through the fusion of INS and GNSS data. Compared to other INS solutions, a MEMS GNSS/INS has a lower size, weight, power consumption and cost. MEMS-based INS are suitable for most applications, including but not limited to: Marine Surveying, Land Surveying, UGVs, Helicopters, Antenna Targeting, Surveying, Robotics, UAVs. This article highlights five key benefits of using MEMS GNSS/INS. What is MEMS GNSS/INS? MINS/GNSS integrated navigation, refers to the fusion of information from both MINS (MEMS INS) and GNSS (Global Navigation Satellite System). This integration combines the strengths of both systems to complement each other and achieve accurate PVA (Position, Velocity, Attitude) results.The advantages and disadvantages of INS and GNSS are complementary. Therefore, combining the two technologies leverages their strengths to provide continuous, high-bandwidth, long-term, and short-term precise, comprehensive navigation parameters. In INS/GNSS or GNSS/INS integrated navigation systems, GNSS measurements suppress the drift of inertial navigation, while INS smooths the GNSS navigation results and compensates for signal interruptions. Five Reasons for Use MEMS GNSS/INS The manufacturing processes for MEMS devices are highly cost-effective due to mass production techniques used in the semiconductor industry. This results in lower production costs, making MEMS INS more affordable for a wide range of aviation applications. A MEMS GNSS/INS is not as costly as a FOG-based (fibre optic gyroscope) INS Lightweight and small By nature, MEMS are built on a miniature scale and measure in micrometres. This makes a MEMS-based INS an ideal fit for vehicles or machines that need a small payload.Take aviation for example, the compact size of MEMS GNSS/INS devices makes them ideal for use in aircraft where space is at a premium. This allows for easier integration into existing systems and more flexibility in aircraft design, potentially freeing up space for additional equipment or cargo. The lightweight nature of MEMS INS contributes to overall weight reduction in aircraft, which is crucial for enhancing fuel efficiency and performance. Lighter navigation systems allow for better payload capacity and improved aircraft range. Flexible placement The more compact nature of MEMS technology also allows the INS to be mounted in variable positions. The compact and efficient nature of MEMS INS makes them suitable for integration with advanced electronics and automation systems. This adaptability supports the development of more sophisticated management systems and enhances the overall functionality of modern aircraft. Low power consumption MEMS technology has advanced to the point where it can reduce power used, utilising power cycling and low power modes. MEMS GNSS/INS devices are designed to consume less power compared to traditional INS solutions. This reduced power consumption is beneficial for the electrical system, leading to lower operational costs and increased energy efficiency. For battery-powered applications, such as unmanned aerial vehicles (UAVs) or smaller aircraft, the lower power consumption of MEMS INS extends mission durations and operational capabilities, enabling longer flights and reducing the need for frequent recharges. GNSS integration With any kind of inertial navigation system, a MEMS GNSS/INS isn’t able to determine absolute position. By itself, the MEMS INS is able to determine the relative position of the vehicle from a known starting point, accounting for distance travelled and orientation. When a MEMS INS is combined with GNSS (global navigation satellite system) it takes advantage of the satellite technology to accurately determine the absolute position on Earth. With these two navigational technologies working in tandem, the strengths of both enable a high level of accuracy. An Excellent Solution Micro-Magic Inc is at the forefront of inertial navigation technology and has recently introduced three GNSS-aided MEMS INS products with varying levels of accuracy (mapping level, tactical level, and industrial level). Notably, the mapping level MEMS INS I3500 features a 2.5°/hr bias instability and a 0.028°/√hr angular random walk, along with a high-precision MEMS accelerometer with a large range (±6g, zero bias instability <30μg). More importantly, in an integrated navigation system, the INS leverages its high short-term accuracy to provide GNSS with continuous and comprehensive navigation information. Conversely, GNSS helps estimate INS error parameters, such as bias, resulting in more precise observations and reduced INS drift. GNSS offers stable long-term accuracy, provides initial values for position and speed, and corrects accumulated errors in the MEMS INS through filtering. The ER-GNSS/MINS-01 stands out as an excellent solution. I3500 High Accuracy 3-Axis Mems Gyro I3500 Inertial Navigation System I3700 High Accuracy Agricultural Gps Tracker Module Consumption Inertial Navigation System Mtk Rtk Gnss Rtk Antenna Rtk Algorithm I6700 Fiber Optic Three Axis Integrated Inertial Navigation System For Intelligent Navigation Fog Gyro Sensor

Key Points Product: GNSS/INS Integrated Navigation Solutions Key Features: Components: Integrated system includes GNSS receiver, Inertial Measurement Unit (IMU), and optional sensors like LiDAR or odometers. Function: Maintains accuracy and stability during GNSS signal loss using additional sensors or motion state constraints like ZUPT. Applications: Ideal for urban navigation, mining, oil logging, and other environments with potential signal obstructions. Inertial Navigation: Utilizes gyroscopes and accelerometers to measure position, velocity, and acceleration. Conclusion: The integrated system’s design is evolving, with solutions that enhance robustness in challenging environments while balancing cost and complexity. In a GNSS/INS integrated navigation system, GNSS measurements play a critical role in correcting the INS. Therefore, the proper functioning of the integrated system depends on the continuity and stability of the satellite signals. However, when the system operates under overpasses, tree canopies, or within urban buildings, the satellite signals can easily be obstructed or interfered with, potentially leading to a loss of lock in the GNSS receiver.This article discusses solutions for maintaining the accuracy and stability of GNSS/INS integrated navigation systems when satellite signals are lost. When the satellite signal is unavailable for an extended period, the lack of GNSS corrections causes the INS errors to accumulate rapidly, especially in systems with lower-precision inertial measurement units. This issue leads to a decline in the accuracy, stability, and continuity of the integrated system’s operation. Consequently, it is essential to address this problem to enhance the robustness of the integrated system in such complex environments. 1.Two Main Solutions to Address Signal Loss of GNSS/INS Currently, there are two main solutions to address the scenario of satellite signal loss. Solution 1: Integrate Additional Sensors On one hand, additional sensors can be integrated into the existing GNSS/INS system, such as odometers, LiDAR, astronomical sensors, and visual sensors. Thus, when satellite signal loss renders the GNSS unavailable, the newly added sensors can provide measurement information and form a new integrated system with the INS to suppress the accumulation of INS errors. The issues with this approach include increased system costs due to the additional sensors and potential design complexity if the new sensors require complex filtering models. Fig.1 System overview of the GNSS IMU ODO LiDAR SLAM integrated navigation system. Solution 2: ZUPT Technology On the other hand, a positioning model with motion state constraints can be established based on the motion characteristics of the vehicle. This method does not require adding new sensors to the existing integrated system, thus avoiding extra costs. When GNSS is unavailable, the new measurement information is provided by the motion state constraints to suppress the INS divergence. For example, when the vehicle is stationary, zero-velocity update (ZUPT) technology can be applied to suppress the accumulation of INS errors. ZUPT is a low-cost and commonly used method to mitigate INS divergence. When the vehicle is stationary, the vehicle’s speed should theoretically be zero. However, due to the accumulation of INS errors over time, the output speed is not zero, so the INS output speed can be used as a measurement of the speed error. Thus, based on the constraint that the vehicle’s speed is zero, a corresponding measurement equation can be established, providing measurement information for the integrated system and suppressing the accumulation of INS errors. Fig.2 The flowchart of the ZUPT-based GNSSIMU tightly coupled algorithm with CERAV. However, the application of ZUPT requires the vehicle to be stationary, making it a static zero-velocity update technology that cannot provide measurement information during normal vehicle maneuvers. In practical applications, this requires the vehicle to frequently stop from a moving state, reducing its maneuverability. Additionally, ZUPT requires accurate detection of the vehicle’s stationary moments. If detection fails, incorrect measurement information may be provided, potentially leading to the failure of this method and even causing the integrated system’s accuracy to decline or diverge. Conclusion The loss of satellite signals can cause rapid error accumulation in the INS, particularly in complex environments like urban areas. Two main solutions are presented: adding additional sensors, such as LiDAR or visual sensors, to provide alternative measurements, or using motion state constraints like Zero-Velocity Update (ZUPT) technology to correct INS errors. Each approach has its own advantages and challenges, with sensor integration increasing costs and complexity, while ZUPT requires the vehicle to be stationary and accurately detected to be effective. Micro-Magic Inc is at the forefront of inertial navigation technology and has recently introduced three GNSS-aided MEMS INS products with varying levels of accuracy ( industrial level,tactical level, and Navigation level). Notably, the Industrial level MEMS GNSS/INS I3500 features a 2.5°/hr bias instability and a 0.028°/√hr angular random walk, along with a high-precision MEMS accelerometer with a large range (±6g, zero bias instability <30μg). I3500 High Accuracy 3-Axis Mems Gyro I3500 Inertial Navigation System   I3700 High Accuracy Agricultural Gps Tracker Module Consumption Inertial Navigation System Mtk Rtk Gnss Rtk Antenna Rtk Algorithm    

Key Points Product: GNSS/MEMS INS Integrated Navigation System Key Features: Components: Combines MEMS inertial sensors with GNSS receivers for enhanced navigation capabilities. Function: Provides high-frequency updates and accurate position, speed, and attitude information by integrating inertial data with GNSS corrections. Applications: Ideal for drones, flight recorders, intelligent unmanned vehicles, and underwater vehicles. Data Fusion: Utilizes Kalman filtering to merge GNSS data with MEMS INS data, correcting accumulated errors and improving overall accuracy. Conclusion: This integrated system leverages the strengths of both technologies to enhance navigation performance and reliability, with wide-ranging applications across various industries. With the development of MEMS inertial devices, the accuracy of MEMS gyroscopes and MEMS accelerometers has gradually improved, leading to rapid advancements in the application of MEMS INS. However, the enhancement in the accuracy of MEMS inertial devices has not been sufficient to meet the increasingly high accuracy demands of MEMS INS. Thus, improving the accuracy of MEMS INS through error compensation algorithms and other methods has become a focus of MEMS INS research. To enhance the performance of MEMS INS, researchers have explored various methods to reduce the errors in these systems. There are four main approaches to reducing MEMS INS errors: Calibration and Compensation of Sensor Error Parameters: This involves using mathematical modeling and experimental tools to stimulate sensor errors, systematically calibrating deterministic errors at the system level, and then compensating for these errors through inertial navigation algorithms to improve overall performance.Rotation Modulation Technology: By applying appropriate rotation modulation schemes, sensor errors can be made to vary periodically without relying on external information sources. This automatic error compensation in the navigation algorithm suppresses the influence of sensor errors on MEMS INS.Inertial Device Redundancy Technology: Due to the low cost of MEMS inertial sensors, redundancy designs can be implemented. Redundancy in sensors can effectively reduce the impact of random errors on MEMS INS, thereby enhancing performance.Incorporating External Information Sources: Using Kalman filtering for integrated navigation to suppress the accumulation of MEMS INS errors. This article will further introduce the fourth method, which is the most practical and widely researched integrated navigation form— the GNSS/MEMS INS integrated navigation system. Reasons for Using GNSS to Assist MEMS INS MEMS INS is a type of dead reckoning system that measures the relative state from the previous to the current sampling moment. It does not rely on acoustic, optical, or electrical signals for measurement, making it highly resistant to external interference and deception. Its autonomy and reliability make it a core navigation system for various carriers such as aircraft, ships, and vehicles. Fig.1 lists the performance of INS of different grades. Fig.1 The Performance Of INS Of Different Grades. MEMS INS offers a high update rate and can output comprehensive state information, including position, speed, attitude, angular velocity, and acceleration, with high short-term navigation accuracy. However, MEMS INS requires additional information sources to initialize position, speed, and attitude, and its pure inertial navigation error accumulates over time, particularly in tactical and commercial-grade INS. The GNSS/MEMS INS combination can realize the complementary advantages of both systems: GNSS provides stable long-term accuracy and can offer initial values for position and speed, correcting the accumulated errors in MEMS INS through filtering. Meanwhile, MEMS INS can enhance the update rate of GNSS navigation output, enrich the types of state information output, and assist in detecting and eliminating GNSS observation faults. Basic Model of GNSS/MEMS INS Integrated Navigation The basic model of GNSS/MEMS INS integration reflects the functional relationship between the observed information from sensors (IMU and receivers) and the carrier navigation parameters (position, speed, and attitude), as well as the types and random models of sensor measurement errors. The carrier’s navigation parameters must be described in a specific reference coordinate system. Fig.2 Basic Model Of Gnssmems Ins Integrated Navigation Navigation problems typically involve two or more coordinate systems: the inertial sensors measure the carrier’s motion relative to inertial space, while the carrier’s navigation parameters (position and speed) are usually described in an Earth-fixed coordinate system for intuitive understanding. Commonly used coordinate systems in GNSS/INS integrated navigation include the Earth-centered inertial coordinate system, the Earth-centered Earth-fixed coordinate system, the local geographic coordinate system, and the body coordinate system. Currently, the algorithms for GNSS/MEMS INS integration in absolute navigation have matured, and many high-performance products have emerged on the market. For example, the three newly launched MEMS INS models by Micro-Magic Inc, shown in the image below, are suitable for applications in drones, flight recorders, intelligent unmanned vehicles, roadbed positioning and orientation, channel detection, unmanned surface vehicles, and underwater vehicles. Fig.3 The Three Newly Launched GNSS/MEMS INS By Micro-Magic Inc I3500 High Accuracy 3-Axis Mems Gyro I3500 Inertial Navigation System   I3700 High Accuracy Agricultural Gps Tracker Module Consumption Inertial Navigation System Mtk Rtk Gnss Rtk Antenna Rtk Algorithm  

Key Points Product: Inertial Navigation System (INS) and Global Positioning System (GPS) Key Features: Components: INS uses accelerometers and gyroscopes; GPS relies on satellite signals. Function: INS provides autonomous navigation without external signals; GPS offers precise geolocation with global coverage. Applications: INS is ideal for underwater, underground, and space; GPS is used in personal navigation, military, and tracking. Integration: Combining INS and GPS enhances accuracy and reliability in complex environments. Conclusion: Choosing between INS and GPS depends on specific needs, with many applications benefiting from their integration for optimal navigation solutions. For complex vehicles such as airplanes, autonomous vehicles, ships, spacecraft, submarines, and UAVs, having an accurate system to maintain and control perfect movement is essential. Two of the most prominent navigation systems in use today are the Inertial Navigation System (INS) and the Global Positioning System (GPS). Both have their unique advantages and applications, but choosing the best system for your needs depends on several factors. This article will explore the differences, strengths, and ideal use cases for each system to help you make an informed decision. Understanding INS and GPS Inertial Navigation System (INS): The MEMS north finder can provide heading information to the moving body in a fully autonomous manner, working without relying on satellites, not affected by climate, and not requiring complex operations. It not only provides the data output interface for the computer, but also provides a good man-machine interface. The MEMS North finder is mainly composed of the inertial measurement module (IMU) and the line part, and the hardware block diagram is shown in Figure 1. Inertial measurement unit (IMU) is composed of gyroscope and rotary mechanism. The circuit part is mainly composed of four circuit boards, including: power board, control board, power amplifier board and base plate. Table 1 shows the components of the north seeking system. Global Positioning System (GPS): The Global Positioning System is a satellite-based navigation system that provides geolocation and time information to a GPS receiver anywhere on or near the Earth where there is an unobstructed line of sight to four or more GPS satellites. GPS is highly accurate and provides continuous positioning information, making it ideal for a wide range of applications, from personal navigation to military operations. However, GPS signals can be obstructed by buildings, trees, or atmospheric conditions, leading to potential inaccuracies. GPS technology is primarily used for location data, mapping, tracking moving objects, navigation, and timing estimations and measurements. However, this information relies on satellite connections, and if the GPS device cannot connect to at least four satellites, the data provided will be insufficient for full operational functionality.   Strengths and Weaknesses INS Strengths: Independence: Does not rely on external signals, making it useful in GPS-denied environments. Instantaneous Response: Provides immediate updates on position and velocity. Robustness: Less susceptible to jamming or signal interference. INS Weaknesses: Drift: Accumulated errors can lead to inaccuracies over time. Complexity: Generally more complex and expensive than GPS systems. Fig.2 Pros And Cons Of Ins And Gnss GPS Strengths: Accuracy: Provides precise location information, often within a few meters. Coverage: Global coverage with continuous updates. Ease of Use: Widely available and relatively inexpensive. GPS Strengths: Signal Dependency: Requires a clear line of sight to satellites, which can be obstructed. Vulnerability: Susceptible to jamming, spoofing, and interference. Combining INS and GPS In many applications, INS and GPS are used together to leverage their complementary strengths. By integrating GPS data with INS, the system can correct for INS drift and provide more reliable and accurate navigation. This combination is particularly valuable in aviation, where continuous and precise navigation is critical, and in autonomous vehicles, where robust and accurate positioning is essential for safe operation. With the rapid development of micro-electromechanical systems (MEMS), smaller and more portable GPS-aided integrated navigation systems have been developed, such as Micro-Magic Inc‘s three models with different accuracy levels. Among them, the ultra-high precision I6600 surveying and tactical-grade system is equipped with a powerful IMU, capable of outputting highly accurate position, velocity, and attitude information. Conclusion Choosing between INS and GPS depends on your specific needs and the environment in which you will be operating. If you require a system that is independent of external signals and can function in challenging environments, INS may be the best choice. However, if you need highly accurate, continuous positioning information with global coverage, GPS is likely the better option. For many applications, combining both systems can provide the optimal solution, ensuring reliability and precision in navigation. By understanding the strengths and limitations of each system, you can make an informed decision and select the navigation system that best meets your requirements.   I6700 MEMS GNSS-Aided Inertial Navigation System    

Key Points Product: I3500 GNSS-Aided MEMS INS Key Features: Components: Cost-efficient MEMS IMU, dual-antenna satellite positioning module, magnetometers, and barometer. Function: Provides high-precision navigation data, maintaining performance during GNSS outages. Applications: Suitable for drones, autonomous navigation, surveying, and motion analysis. Inertial Navigation: Combines inertial measurements for position, velocity, and attitude calculation. Conclusion: The I3500 exemplifies the integration of MEMS INS and GNSS, enhancing navigation reliability and accuracy across various sectors.   MINS/GNSS integrated navigation, refers to the fusion of information from both MINS (MEMS INS) and GNSS (Global Navigation Satellite System). This integration combines the strengths of both systems to complement each other and achieve accurate PVA (Position, Velocity, Attitude) results. Classification of MEMS Inertial Navigation Systems After more than 30 years of development, MEMS inertial technology has advanced rapidly and seen wide application. Various practical MEMS inertial devices and MEMS INS have emerged, finding extensive use in fields such as aerospace, maritime, and automotive industries. Tactical-grade MEMS gyroscopes (with bias stability of 0.1°/h to 10°/h, 1σ) and high-precision MEMS accelerometers (with bias stability of 10⁻⁵g to 10⁻⁶g, 1σ) have marked the entry of tactical-grade MEMS INS into the model application stage. Generally, MEMS inertial systems can be classified into three levels: Inertial Sensors Assembly (ISA), Inertial Measurement Unit (IMU), and Inertial Navigation System (INS), as illustrated in Figure 1. Fig.1 Three Levels Of Mems Ins (2) MEMS ISA: Comprised solely of three MEMS gyroscopes and three MEMS accelerometers, it lacks the capability to operate independently. MEMS IMU: Builds on the MEMS ISA by adding A/D converters, mathematical processing chips, and specific programs, enabling it to independently collect and process inertial information. MEMS INS: Further expands on the MEMS IMU by incorporating coordinate transformation, filtering processes, and auxiliary modules, which typically include magnetometers and GNSS receiver boards. Auxiliary sensors like magnetometers are particularly significant in aiding MEMS INS alignment and enhancing performance. The three newly launched MEMS INS (Micro-Magic Inc-Mechanical System Inertial Navigation System) models by Ericco, shown in the image below, are suitable for applications in drones, flight recorders, intelligent unmanned vehicles, roadbed positioning and orientation, channel detection, unmanned surface vehicles, and underwater vehicles. Fig.2 The Three Newly Launched Mems Ins Models By Ericco How GNSS-Aided MEMS INS Works GNSS provides users with all-weather, high-precision absolute position and time information, while inertial navigation systems (INS) offer high short-term resolution and strong autonomy. Their complementary characteristics enhance overall performance: INS can leverage its high short-term accuracy to provide GNSS with more continuous and complete navigation information, while GNSS can help estimate INS error parameters like bias, thus obtaining more precise observations and reducing INS drift. Fig.3 Three Levels Of Mems Ins Specifically, GNSS uses signals from orbiting satellites to calculate position, time, and velocity. As long as the antenna has a line-of-sight connection with at least four satellites, GNSS navigation achieves excellent accuracy. When satellite visibility is obstructed by obstacles like trees or buildings, navigation becomes unreliable or impossible. INS calculates relative position changes over time using angular rate and acceleration information from the inertial measurement unit (IMU). The IMU comprises six complementary sensors arranged on three orthogonal axes. Each axis has an accelerometer and a gyroscope. Accelerometers measure linear acceleration, while gyroscopes measure rotational rate. With these sensors, the IMU can accurately measure its relative motion in 3D space. INS uses these measurements to compute position and velocity. Another advantage of IMU measurements is that they provide angular solutions about the three axes. INS converts these angular solutions into local attitudes (roll, pitch, and yaw), providing this data along with position and velocity. Fig.4 The Inertial Measurement Unit Body Coordinate System Real-Time Kinematic (RTK) is a mature high-precision positioning algorithm of GNSS, capable of achieving centimeter-level accuracy in open environments. However, in complex urban environments, signal obstructions and interferences reduce the ambiguity fixing rate, leading to decreased positioning capability. Therefore, researching GNSS RTK and INS integrated positioning systems is crucial for fields such as autonomous navigation, surveying and mapping, and motion analysis. I3500 newly launched by Micro-Magic Inc is a Cost-efficient GNSS aided MEMS INS with a highly reliable MEMS IMU and a dual-antenna full-system full-band positioning and directional satellite module. It also integrates magnetometers and a barometer, which can calculate the size of the attitude Angle and help the drone navigate to the desired altitude. Conclusion Integrating MEMS Inertial Navigation Systems (INS) with GNSS technology significantly enhances navigation accuracy by combining their strengths. MEMS INS, with its rapid advancement, is now widely used in aerospace, maritime, and automotive industries. GNSS provides precise positioning, while MEMS INS ensures continuous navigation, even during GNSS outages. The I3500 by Micro-Magic Inc exemplifies this integration, offering high-precision navigation data, ideal for autonomous navigation, surveying, and motion analysis. In summary, GNSS and MEMS INS integration revolutionizes navigation by improving accuracy, reliability, and versatility across various applications.   I3500 High Accuracy 3-Axis Mems Gyro I3500 Inertial Navigation System