Waveform Selection for Multistatic LSS Target Tracking with Rao-Blackwellized Particle Filter

In this paper, to track the Low-Altitude and Slow-speed Small target (LSS), we use the Rao-Blackwellized particle filter (RBPF) algorithm as a basis to investigate the waveform selection problem arising from its application to target multi-station tracking. Waveforms are designed or selected to ensure a small measurement error in the dimension of the target motion state, to optimize radar performance, and to cope with the non-smoothness and uncertainty of the environment. RBPF is not only suitable for complex nonlinear systems, but also reduces the dimensionality of particle filter states and reduces computational complexity. The algorithm is verified by simulation, and the results show that the RBPF algorithm can complete the target multi-station tracking task well and have good performance.