Tracking Number Time-Varying Nonlinear Targets Based on SQUF-GMPHDA in Radar Networking

For the problem that detecting and tracking targets in false alarm and clutter area (RNWT) is under constraints that motion model and measurement model are both nonlinear, firstly square root unscented filter algorithm (SQUFA) is used in nonlinear tracking in multi-radar networking. Then SQUFA is introduced to GMPHDA to form square root unscented filter Gaussian mixture probability hypothesis density filter algorithm (SQUF-GMPHDA), where newborn targets, spawn targets and existing targets are independently sampled, predicted and updated based on SQUFA. So the problem of high-precisely tracking RNWT under nonlinear condition is solved.