Self-adaption strong tracking unscented kalman filter (UKF) positioning filter algorithm based on fuzzy logic

Abstract

The invention discloses a self-adaption strong tracking unscented kalman filter (UKF) positioning filter algorithm based on fuzzy logic. The self-adaption strong tracking UKF positioning filter algorithm comprises the steps that: (1) a positioning filter model is built; (2) initial parameters of a filter are set; (3) the state quantity is subjected to filtering by adopting the UKF filter algorithm; (4) a fuzzy logic system is used for solving softening factors in the self-adaption tracking algorithm; (5) the self-adaption factors in the strong tracking self-adaption algorithm are solved; and (6) the epoch moment is increased by 1, the next moment observation is read, and the operation returns to the step (4) until the operation is completed. The strong tracking self-adaption algorithm in introduced on the basis of the UKF filter algorithm, in addition, a novel recursive algorithm is adopted in the strong tracking self-adaption algorithm for estimating the information covariance matrix, and the softening factors in the strong tracking algorithm are solved through a fuzzy logic reasoning system and are estimated in real time according to the work state of an epoch moment filter. The estimation is carried out in satellite navigation user receiver position estimation, and the positioning performance and the capability of carriers adapting to the dynamics can be greatly improved.

Description

technical field [0001] The invention relates to the calculation of position parameters of a satellite navigation receiver, in particular to an adaptive strong tracking UKF positioning filter algorithm based on fuzzy logic. Background technique [0002] The rapid development of satellite navigation technology has gradually replaced traditional navigation technologies such as radio navigation and celestial navigation, and has become a widely used navigation and positioning technology, and has made great progress in accuracy, real-time, all-weather and other aspects. At present, many countries and regions in the world have established or are building global satellite positioning and navigation systems, including the GPS system established by the United States, the GLONASS system established by Russia, the "Galileo" system under construction by the European Union, and the "Beidou II" system under construction by China. generation" system. The positioning calculation module in t...

AI Technical Summary

Problems solved by technology

[0006] Although the least squares algorithm is simple, due to the lack of consideration of the system dynamic state, the estimation accuracy is not very high, especially for the non-stationary motion state, there is a large estimation error

Although the Kalman filter algorithm can solve the nonlinear problem in positioning calculation, it has extremely strict requirements on prior information, and the positioning accuracy is limited by the dynamics of the carrier.

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