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Fast Direct-Position-Determination based on PSO

The Direct Position Determination (DPD) methods are widely employed in ditributed radar systems, especially under low signal-to-noise ratio (SNR) scenarios. However, the DPD methods usually require exhaustive search resulting in insufferable computational complexity. In this paper, a fast DPD based on particle group optimization (termed PSO-DPD) is proposed to solve this problem under Neyman-Pearson (NP) criteria. Specifically, the proposed method formulates the D-PD problem as a non-convex optimization problem and then solves this problem by employing the PSO method. Further-more, our algorithm is considered under the assumption that each node is spatially coherent and noncoherent, respectively. Simulation results demonstrate that the proposed algorithm reduces computational complexity rapidly compared with the exhaustive-search one. In addition, the positioning accuracy of our method is comparable to the exhaustive-search one.