Collaborative Detection and Tracking of Stealthy Target by Netted Radar

Focusing on the radar allocation for stealth targets detection and tracking issue in air-defense radar network, a novel collaborative detection and tracking algorithm that combines Binary Particle Swarm Optimization (BPSO) and particle filtering to cope with the radar allocation is proposed in this paper. In the proposed algorithm, Radar Allocation Schemes (RAS) are designed according to the characters of stealthy targets, and the particles distributed randomly are applied to obtain the detection probability of newborn targets. Then the tracking accuracy is measured by the Posterior Cramr-Rao Lower Bound (PCRLB) of the tracked targets. Moreover, the BPSO is selected to search the whole RAS, and the results of particle filtering of the selected tracking radars are fused. Simulation results show that the proposed method can not only quickly identify newborn targets, but also optimize the tracking performance of the existing targets, and improve the tracking accuracy of the whole radar network compared with traditional methods.