Estimation Method of Direct Signal Parameters and Multipath Signal Numbers and Parameters of Satellite Navigation

Abstract

The present invention relates to a method for estimating the parameters of satellite navigation direct signals and the number and parameters of multipath signals. The technical feature is that the Dirichlet process DP(α, G0) is used as the prior distribution of the number M of multipath signals, and the distribution of M conforms to Dirichlet process: obtain the possible number of multipath signals according to this prior distribution sampling; According to the possible number of multipath signals, construct the state equation x(k+1)=Fx(k+1)=Fx( k)+w(k) and the observation equation y=aR(τ)+n of the observation vector; according to the possible number of multipath signals and the state equation and observation equation, the parameters of the direct signal and the multipath signal are estimated by the particle filter method , and the number of multipaths can be determined at the same time. The present invention can estimate the number and parameters of multipath signals without knowing the number of multipath signals, and is not only applicable to the situation that the direct signal is larger than the multipath signal, but also applicable to the situation that the direct signal is smaller than the multipath signal.

Description

technical field [0001] The invention relates to a method for estimating the number and parameters of satellite navigation direct signal parameters and multipath signals, belonging to a satellite navigation signal processing method. Background technique [0002] The satellite navigation multipath signal estimation method eliminates the influence of the multipath error of the satellite navigation system (including GPS, GLONASS, GALILEO, Beidou system, etc.) on the positioning results by estimating the multipath signal. [0003] The research on estimation methods of satellite navigation multipath signals is divided into estimation methods based on maximum likelihood and methods based on Bayesian estimation. The method based on maximum likelihood estimation finds the optimal estimated value of the parameters by maximizing the likelihood function. For this method, refer to "K.Kaindl, N.Niklasch, Improving Path Separation in a Multipath Environment by Applying Nonlinear Estimation...

AI Technical Summary

Problems solved by technology

In the actual environment, such as urban areas where multipath has a large impact, when the carrier carrying the receiver moves, the multipath reflections from reflectors such as buildings and vehicles are constantly changing, so it is difficult to determine at a certain moment the number of multipath signals, in which case applying existing methods can lead to large errors