Motion Compensation for Synthetic Aperture Passive Localization Based on Weather Radar Signals

In emitter localization, the synthetic aperture positioning technique can achieve high-precision positioning even at a low signal-to-noise ratio (SNR). However, existing methods overlook the impact of receiver motion errors on the phase history of the received signal, leading to a reduction in localization accuracy. In this study, we propose a motion compensation (MoCo) technique for synthetic aperture passive localization using weather radar signals. Weather radar stations are chosen as reference stations due to their widespread coverage, high transmission power, and continuous signal transmission. The proposed method involves estimating and compensating for phase errors in the received signal, enabling phase coherency accumulation and achieving high-precision emitter localization. First, pulse compression is applied to the received weather radar signals to extract the phase information containing motion error details. Subsequently, we estimate motion errors using the extracted radar signal phase and apply phase compensation to the emitter target signal. Finally, the existing synthetic aperture positioning method is used to estimate the position of the target. Simulation results demonstrate that the method proposed in this paper offers superior accuracy in emitter localization compared to relying solely on real-time kinematic (RTK) for MoCo. The effectiveness of our proposed method is validated through actual unmanned aerial vehicle (UAV) experiments.