Kalman filtering moving target positioning method based on inertial navigation system assisted single satellite positioning

Abstract

The invention provides a Kalman filtering moving target positioning method based on inertial navigation system assisted single satellite positioning. The method comprises three parts: least squares-Newton iteration single satellite positioning initial solution, INS displacement compensation and Kalman filtering fusion feedback, wherein the least squares-Newton iteration single satellite positioning initial solution part constructs a single satellite running orbit to obtain single satellite ephemeris data; a target positioning initial solution is solved by using pseudo-distance values measuredat three times between a satellite and a ground positioning target and the least squares method; and a areal result is further approached by using the Newton iteration; secondly, real-time displacement of the target is output and feedbacked to least squares and a subsequent Kalman filtering by using the INS part to correct the result; finally, the Kalman filtering is performed and advantages of high accuracy and robustness of the unscented Kalman filtering (UKF) is taken. After the positional position iteration and fusion filtering, the target positioning result is obtained, the positioning accuracy of single satellite navigation in a dynamic environment can be effectively improved and stable positioning can be maintained for a long time.

Description

technical field [0001] The invention is a Kalman filter moving target positioning method based on inertial navigation assisted single-satellite positioning, and particularly relates to least squares-Newton iteration (Least squares-Newton iteration), inertial navigation system (INS) assisted positioning and Kalman filter ( KF) fusion method. Background technique [0002] Today's satellite positioning technology has matured, and major countries or regions have their own satellite navigation and positioning systems, which can provide users with fast and high-precision positioning services. But today's satellite navigation systems are all based on satellite constellations, using pseudo-range measurements for positioning, requiring at least four well-arranged satellites to achieve a single positioning, which is a sophisticated and complex system. It is precisely because of its precision and complexity that the system itself is very fragile. Once the key node satellites are lost,...

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Problems solved by technology

[0010] Aiming at the problems that the existing single-satellite navigation and positioning system has poor positioning accuracy, poor positioning stability, and difficulty in realizing dynamic target positioning, the present invention proposes a Kalman filter moving target positioning method based on inertial navigation-assisted single-satellite positioning, which mainly includes The least squares-Newton iterative single-satellite positioning initial solution, INS inertial navigation displacement compensation and Kalman filter fusion feedback are three components: the least-squares-Newton iterative single-satellite positioning initial solution part requires the construction of a single-satellite orbit in advance To obtain the single ephemeris data, use the measured pseudo-range values ​​of the satellite relative to the ground positioning target at three moments, use the least square method to solve the initial solution of the target positioning, and use Newton iteration to further approach the real result; secondly, because the target is in a moving state , the above least squares requires the INS inertial navigation part to output the real-time displacement of the target to be fed back to the least squares and the subsequent Kalman filter to correct the results; finally, the Kalman filter part, due to the continuity of the position change of the positioning target, plays an unlimited role. With the advantages of high precision and strong robustness of the trace Kalman filter (UKF), the positioning result of the target is obtained after positioning position iteration and fusion filtering, which can effectively improve the positioning accuracy of single-satellite navigation in a dynamic environment and maintain it for a long time stable positioning

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