GNSS IMU MM vehicle integrated navigation system
Foreword: In recent years, with the rapid development of positioning business, users have put forward higher and higher requirements for vehicle-mounted positioning accuracy. The original navigation level is gradually replaced by the lane level. Especially in urban canyon environments (high buildings, elevated buildings), users cannot receive GNSS signals or the GNSS signals are interfered with, resulting in no GNSS positioning results or poor positioning accuracy. This is an inherent shortcoming of "active positioning" and cannot be overcome algorithmically. In response to this problem, multi-sensor fusion solutions such as GNSS IMU are receiving more and more attention, because "passive positioning" IMU can just make up for the shortcomings of satellite positioning.
Basic principles
Navigation Satellite System (GNSS)
Global Navigation Satellite System (Global Navigation Satellite System) is a pseudo-range carrier that relies on satellites. A space-based radio navigation system that uses ephemeris, time, clock offset and other information for real-time positioning, and can provide users with all-weather three-dimensional coordinates, speed and time information at any location on the earth's surface or near-Earth space. The advantages of the GNSS system are high accuracy and stable and non-divergent errors, but it is easily affected by the surrounding environment, such as obstruction by trees and buildings, and multipath effects caused by highly reflective objects such as mirrors.
Inertial Navigation System (IMU)
Inertial Navigation System (Inertial Navigation System) is a system that does not rely on external information and does not radiate energy to the outside (such as radio navigation). Autonomous navigation systems mainly use inertial measurement units (IMUs). Its working environment includes not only the air and the ground, but also underwater. The basic working principle of inertial navigation is based on Newton's laws of mechanics. By measuring the acceleration of the carrier in the inertial reference system, integrating it over time, and transforming it into the navigation coordinate system, we can obtain the acceleration in the navigation coordinate system. Information such as speed, yaw angle and position. The advantage is that the work does not require communication, the installation position is arbitrary, and the positioning range is full scene, but the positioning accuracy is not high, and the error diverges over time. Complementary to GNSS navigation systems.
Map matching technology (MM)
Map matching technology MM (Map matching) combines user location information and map data to calculate the user's accurate position on the road on the map to assist vehicle navigation. precise control.
Dead Reckoning (DR)
Dead Reckoning DR (Dead Reckoning) is a tracking and navigation algorithm that relies on inertia on the premise of obtaining the current coordinate position of the carrier. The measurement unit IMU obtains the distance and orientation of the carrier movement in the same period, and then calculates the position at the next moment. In the introduction of this article, we mainly talk about the algorithm of IMU-assisted integrated navigation based on the existing GNSS system solution.
Pain points of vehicle positioning
Vehicle navigation and positioning have been developed for a long time, but as accuracy requirements become higher and higher, some problems with vehicle positioning have gradually emerged:
Yaw recalculation: refers to position point drift caused by signal obstruction on elevated roads or urban canyons;
Unable to locate: refers to low accuracy of calculation in no-signal areas (parking lots, tunnels), resulting in exit The error is large;
Road grasping error: refers to the main and auxiliary road, elevated road grasping error up and down.
Among them, yaw recalculation and inability to position are mainly determined by the GNSS positioning principle. GNSS positioning accuracy is affected by the observation environment and is difficult to improve; for road grasping errors, the direct cause is that the correct road and the wrong road are too close together. , cannot be distinguished due to the limitation of positioning accuracy; the fundamental reason is that only location information is used for road grabbing, and the value of other data is not used.
Technical Solution
Among the key technologies introduced above, each has its own strengths and complements each other in terms of scene coverage and accuracy.
Based on the integration of these three mainstream positioning technologies, the GNSS IMU MM solution is proposed, relying on algorithm (DR) data (POS/HEAD) to improve positioning reliability.
From the above-mentioned major problems of vehicle positioning, they can be solved step by step:
Data fusion: This part mainly calculates the position, speed, time and heading information output by the GNSS module. The data is transferred to the data processing terminal for real-time data fusion calculation to determine the quality of the current GNSS data, and different positioning judgment strategies are combined according to the data quality.
Device compensation: When the GNSS signal quality is poor or positioning cannot be performed, the IMU's DR algorithm can only be relied upon for compensation. The main function of the compensation module is to use GNSS data to compensate the speed sensor error parameter (scale factor) and the IMU error parameter (gyro scale factor and gyroscope three-axis bias). The purpose of compensation is that in scenarios where there is no GPS signal or weak GPS signal, relatively reliable navigation information can be obtained by relying only on the DR algorithm (usually centimeter-level positioning can be guaranteed in a short time).
Scene recognition: Relying on the built-in scene map data source and the environmental information collected by real-time external sensors to determine the scene, determine the carrier map position at the moment, and assist the system in making behavioral judgments about the surrounding environment. Generally, high-precision street view map sources, lidar and millimeter wave radar are used for environmental perception.
Taking the K8 module as an example, it adopts an adaptive integrated navigation design, supports RTCM2.X/3.X differential data format access, and can achieve centimeter-level positioning accuracy in open environments; built-in integrated inertial navigation module, which can achieve high-precision navigation in complex environments.
Relying on the independently developed high-precision positioning algorithm and based on the current operating environment of the vehicle carrier, the system adaptively evaluates the current satellite quality and performs integrated navigation based on the satellite quality.
When the satellite conditions are good, satellite navigation is mainly used, combined with the high-precision RTK algorithm, the real-time positioning accuracy is ≤±2.5cm, and the speed measurement accuracy is better than 0.03m/s; when the satellite navigation fails to work normally, Led by inertial navigation, the accuracy remains centimeter-level within 3 seconds and meter-level within 10 seconds.