A Rigorous Backnavigation Method for Optimal Estimated Fine Alignment

Abstract

The invention provides a strict reverse navigation method for optimal estimation fine alignment, comprising: establishing an adaptive control function; a forward navigation calculation process; a reverse navigation calculation process; and performing adaptive control on the number of forward and reverse calculations. The present invention shortens the alignment time of the optimal estimated fine alignment on the basis of ensuring the alignment accuracy. The method proposed by the present invention can effectively solve the problem that the initial value error of the filter in the initial stage of the optimal estimated fine alignment affects the subsequent convergence speed. In the initial stage, a large number of forward and reverse navigation solutions are used to reduce the initial error as much as possible and improve the filtering convergence speed. In the subsequent stages, as the filtering accuracy continues to improve, the number of forward and reverse navigation gradually decreases. Since the reverse calculation is a strictly reverse process, the approximation error is effectively avoided, and the error will not be enlarged after multiple forward and reverse calculations, which will speed up the subsequent convergence speed. The present invention adopts an adaptive method to control the number of forward and reverse navigation solutions, thereby controlling the amount of calculation.

Description

technical field [0001] The invention belongs to the technical field of navigation and relates to a strict reverse navigation method for optimal estimation fine alignment. Background technique [0002] The usual navigation calculation process is to treat the sampling data of the gyroscope and accelerometer in the strapdown inertial navigation system as a set of time series and process them sequentially. This process is real-time and does not need to store the data. With the continuous development of contemporary computer technology, its data storage capacity and computing power have been greatly improved. It can be considered to store the sampling data during the entire navigation process. In addition to the conventional forward operation, the stored data can also be Process in reverse chronological order. In navigation scenarios without real-time requirements, repeated forward and reverse analysis and calculation of the stored data is beneficial to improve navigation accura...

AI Technical Summary

Problems solved by technology

The method of the present invention performs self-adaptive control on the number of forward and reverse navigation solutions in different time periods during the alignment process

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