Parameter integration filter and parameter decomposition filter for Autonomous Navigation of BDS

Autonomous Navigation (AutoNav) based on inter-satellite cross-link can substantially maintain BDS survivability in war and alleviate the need of the Operational Control Segment. It plays a major role in the implementation of the global capabilities of BDS. There are two kinds of filters used in AutoNav, namely the parameter integration filter (PIF) and the parameter decomposition filter (PDF). In order to discuss which filter is better suitable for AutoNav, we compare observation equations of the PIF and PDF and analyze the performance of AutoNav implemented by the two filters. In detail, first, we compare the one-way observation equation of the PIF and the two-way combined observation equations of the PDF regarding number of redundant observations, computational cost and observation errors. Then, with the simulation of the BDS constellation, we implement AutoNav by the PIF and PDF and analyze the performances of the two filters regarding precision, computational efficiency and parameter correlation. The results show that the PIF and PDF can achieve equivalent precision, but the solution time of the PDF is less than half of that of the PIF.