Ballistic target tracking based on quasi-Monte Carlo filtering

Abstract

In this paper, we propose a new sequential quasi-Monte Carlo (SQMC) filtering algorithm for ballistic target tracking in the reentry phase. The central idea of the new algorithm is to apply number theoretic sampling method to SQMC. The point set of uniform distribution generated by cyclotomic field can construct more uniform scattered points in unit cube. Therefore, random samples generated by the point set of uniform distribution can adequately describe the posterior probability density function (PDF). Simulation results show that the proposed filtering algorithm provides better performance in tracking accuracy when compared to SMC, SQMC using Halton sequence.