Spatio-Temporal Alignment for Networked Radars on Moving Platforms Based on Discrete Cosine Transform

For networked radars on moving platforms, registration errors caused by time-varying relative positions and orientation angles deteriorate the target tracking accuracy significantly. In this paper, a spatio-temporal alignment method is proposed for networked radars on moving platforms by sharing the only parameter of Coherent Processing Intervals (CPIs). The time-varying spatio-temporal alignment parameters of moving radars are modelled as linear expressions of Discrete Cosine Transform (DCT) basis functions. The proposed method does not require the knowledge of positions and orientation angles of moving radars at each sample time and is suitable for asynchronous measurements from networked radars. For the registration objective function, the alignment parameter estimation using the steepest descent method is derived. In order to solve the problem of local optimal solution caused by the non-convexity of the objective function, a filling matrix based method for solving the global optimal solution of the registration function is proposed. Furthermore, the Cramér-Rao lower bound (CRLB) of the alignment parameter is derived for moving radars, which is compared with estimation errors of parameters. Simulation results show that this proposed alignment algorithm for moving radars improves the target tracking performance compared with the existing methods.