Application of particle filter with uniform resampling on SINS initial alignment

In order to solve the problem that traditional particle filter algorithm often collapses to a single point, this paper proposed a new particle filter algorithm by adding the uniform sampling algorithm to the random resampling. The uniform resampling algorithm improved the diversity of the particles in particle filter by inheriting the distributing bound of the abandoned particles. Then, this particle filter algorithm with uniform resampling was used to research the SINS non-Gauss and non-linear alignment problem. Simulated data show that the particle filter algorithm with uniform resampling results in more accurate alignment then the standard particle filter and improves the stability of the SINS alignment algorithm.