Passive stationary target positioning using adaptive particle filter with TDOA and FDOA measurements

Combined measurement with TDOA and FDOA is a promising technique in passive localization. However, this method likely demands massive computations, while leads to inaccurate results due to difficult linear approximation. In this paper, a new algorithm based upon an adaptive particle filter is proposed. This algorithm may converge to a desired result in real-time by using only a few particles. Simulation results show that, compared with traditional methods, the new method may achieve significant improvement in the accuracy of localization while reaching the Cramer-Rao lower bound (CRLB) in low noise level conditions.