Rotated Array Radar on Non-Dedicated Platforms: A Processing Method under Rotation Velocity Errors

This paper presents rotated array radar (RAR), a new paradigm that innovatively leverages non-dedicated rotating structures as carrier platforms. Motivated by aerodynamic-induced fluctuations and the practical lack of high-fidelity trajectory monitors on such non-dedicated platforms, rotation is modeled with a periodic angular deviation with unknown parameters. A sharpness-driven autofocus approach is proposed to estimate these parameters to facilitate subsequent motion error compensation. Moreover, to efficiently process the resulting non-Cartesian array samples produced by RAR, a non-uniform fast Fourier transform (NUFFT) imaging algorithm is introduced. Extensive simulations over diverse parameter settings demonstrate that the recovered rotation trajectories closely approximate the true deviations, achieving estimation errors on the order of a few percent across the tested cases (mean error 2.5–5.1%) and supporting the robustness of the proposed pipeline. Simulations driven by real wind-turbine monitoring data support the practicality of the motion error model and demonstrate the effectiveness of the proposed methods under realistic trajectories. Finally, an application case is investigated with a pulsed RAR for range-velocity-angle estimation of targets.