Joint Trajectory Optimization and Power Allocation for Target Tracking in Airborne Radar Network with Missing Data

In this paper, an effective joint trajectory optimization and power allocation (JTOPA) scheme is proposed for target tracking in airborne radar network with missing data. Missing data may occur during data exchanging between radar nodes and a fusion center (FC) due to unreliability of communication channels. In the presence of missing data, we derive the posterior Cramér-Rao lower bound (PCRLB) to evaluate the target tracking performance. On this basis, to maximize the target tracking performance while ensuring the practical constraints of the airborne radar kinetics and resource allocation, we formulate the JTOPA optimization problem. To tackle the JTOPA problem, we design an efficient two-stage solution technique, and decompose the optimization problem into two sub-problems, which can be solved by the nonmonotone spectral projected gradient (NSPG) method. Simulation results demonstrate that the proposed JTOPA achieve significantly better target tracking performance as compared with other benchmark schemes.