Robust Capon Beamforming for UAV-Borne Distributed Phased-MIMO Array Radar

Unmanned aerial vehicles (UAVs) swarm, with each UAV equipped with a phased array, can form an extremely large distributed radar array, thus achieving high spatial resolution and improved detection performance. The most critical challenge for UAV-borne distributed array is that the inevitable platform jitter and drift cause positional perturbation, in turn degrading the array performance. To counteract this issue, this paper analyzes the positional perturbations in UAV-borne distributed phased multiple-input multiple-output (phased-MIMO) array radar and proposes a robust Capon beamformer. Specifically, by exploiting the group positional perturbation structure in the virtual array formed via matched filtering of phased-MIMO array, we propose a robust Capon beamformer seeking to maximize the beamformer output signal power regardless of UAVs positional perturbations. A Dinkelbach-based algorithm combined with modified semidefinite relaxation (SDR) and rankone approximation is employed to iteratively solve the formulated non-convex fractional quadratically constrained quadratic programming (FQCQP) problem. Numerical simulations validate the superior robustness of the proposed beamformer in handling group positional perturbations caused by UAV platform.