A Hybrid Integration Method for Low-Observable Micro-UAV Trajectory Tracking by 2D MIMO Radar

It is quite challenging for the micro-unmanned aerial vehicle (UAV) which is in low-observable environments and has minor radar cross section (RCS) to detect and track. Accordingly, a hybrid method of coherent and noncoherent integration is proposed for micro-UAV tracking under poor signal-to-noise ratio (SNR) surroundings by 2-dimensional (2D) multiple-input multiple-output (MIMO) radar with range, Doppler, azimuth and pitch. Firstly, for rectifying the range walk caused by long-term energy accumulation, this paper introduces keystone transform (KT) to eliminate the coupling terms of echo signals. On this foundation, for improving the detection and tracking performance of low-observable micro-UAV, the radar raw 4D measurements are directly utilized to integrate the detection and tracking processes aided by the track-before-detect (TBD) strategy, which avoids the information lack of weak targets caused by traditional tracking methods based on thresholds. Finally, simulation results indicate the approach in this paper corrects the range walk and has distinct superiorities over traditional approaches for trajectory tracking of micro-UAV under low SNR conditions.