Phase Compensation Based Multi-frame Coherent Integration for Drone Detection with Radar

Abstract

In order to improve the detection ability of small and weak targets such as drones, a multi-frame coherent integration(MFCI) method based on phase compensation is proposed. The phase information of the multi-frame radar echoes is first analyzed and the maximum likelihood estimation(MLE) model of the motion parameters is established. Due to the target motion, the phenomena of migration through range and Doppler cells will occur in the successive frames of target echoes. In order to achieve coherent integration in multiple frames, all the orientations of the multi-frame signal are searched within a certain initial radial velocity and radial acceleration range. The trajectory of each moving target and the corresponding motion parameter values are then obtained, while the phase of the multi-frame signal is located in the same range and the Doppler cell corresponding to a target, thereby improving the detection performance of the weak targets. To further reduce the amount of computation, the influence of radial acceleration on the detection performance of weak targets is studied. Simulation and measured data experiments show that the proposed algorithm can accurately detect drones with less computational complexity.