Multi-UAV Collaborative Trajectory Optimization for Asynchronous 3-D Passive Multitarget Tracking

This article considers the 3-D collaborative trajectory optimization (CTO) of multiple unmanned aerial vehicles to improve multitarget tracking performance with an asynchronous angle arrival measurements. The predicted conditional Cramér–Rao lower bound is adopted as a measure predict and subsequently control error online. Then, CTO problem cast time-varying nonconvex subjected constraints arising from dynamic security (height, collision, obstacle/target/threat avoidance). Finally, comprehensive solution method (CSM) presented tackle resulting problem, according its unique structures. Specifically, if all are inactive, can be simplified convex constraints, which solved by nonmonotone spectral projected gradient (NSPG) method. Oppositely, alternating direction penalty (ADPM) solve some positive constraints. ADPM introduces auxiliary vectors decouple complex separates into several subproblems tackles them alternately, while locally adjusting factor at each iteration. We show subproblem w.r.t. position vector but efficiently NSPG separable have closed-form solutions. Simulation results demonstrate that CSM outperforms unoptimized in terms performance. Besides, achieves near-optimal provided genetic algorithm much computational complexity.