Self-adaptive vehicle-mounted integrated navigation and positioning method

Abstract

The invention discloses a self-adaptive vehicle-mounted integrated navigation and positioning method, which comprises the steps of performing multi-sensor information fusion on a satellite positioning system and a strapdown inertial navigation system, constructing an adjustment factor according to factors such as satellite positioning quality on the basis of a standard integrated navigation system, and performing real-time self-adaptive adjustment on a system observation noise array, that is, constructing a self-adaptive GPS / INS Kalman filtering algorithm, thereby being capable of obtaining the position, the speed, the attitude, the acceleration, the angular velocity and other information of the high-precision vehicle in any complex environment. The method is high in real-time performance and good in robustness.

Description

technical field [0001] The invention relates to the technical field of car navigation, in particular to an adaptive vehicle integrated navigation positioning method. Background technique [0002] Satellite navigation is currently the most widely used positioning technology, with high positioning and speed measurement accuracy, and good long-term working stability. However, in many complex environments (underpasses, tunnels, garages), satellite positioning often has problems such as multipath interference, satellite signals being blocked or out of lock, or even unable to locate or have large positioning errors, so it cannot work. [0003] Strapdown inertial navigation system, referred to as inertial navigation system, is a completely autonomous navigation system. It can continuously provide information such as the position, velocity, attitude, acceleration and angular velocity of the carrier. It has good stability in a short time, is easy to use, and is low in cost. [0004]...

AI Technical Summary

Problems solved by technology

[0004] Based on the above analysis, Kalman filter technology can be used to fuse satellite positioning and inertial positioning to obtain vehicle position information and speed information in various environments, so as to achieve high-performance navigation and positioning. However, a large number of studies have shown that, In the low-cost integrated navigation system, the satellite receiver will be interfered by buildings, clouds and electromagnetic interference, resulting in frequent changes in measurement noise. Therefore, real-time measurement information must be used to correct the integrated navigation system in real time. However, the commonly used adaptive integrated navigation Filtering algorithms often use new information for settlement, and the amount of calculation is large, so it is difficult to ensure real-time performance

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