基于高度角随机模型的GNSS外辐射源雷达定位算法

An elevation-dependent stochastic localization algorithm is proposed to address the problem of different satellites contributing differently to the localization error in Global Navigation Satellite System (GNSS)-based passive radar. Herein, the Cramer-Rao Lower Bound (CRLB) and statistical characteristics of the target position estimator are theoretically analyzed, and the contributions of satellite position and ground-station position errors to passive localization error are calculated. Simulation results show that the proposed algorithm can reasonably distribute the error from the pseudo-range measurements of multiple GNSS satellites with different directions and reflective paths. The localization performance reaches the CRLB but will not deteriorate considerably due to a change in the star selection scheme. Analysis of the ground-station position and satellite position errors show that their contributions to the total positioning error can be ignored if the standard deviation of the ground-station position is less than 10 cm and that of the satellite position is less than 1 km.