An Extended Target Detector Using Image-Processing Techniques Exploiting Energy-Spillover Phenomenon in Radar Echoes

This article presents an extended radar target detection algorithm based on image features that exploits the energy-spillover phenomenon. The algorithm uses the target energy-spillover effect effectively to improve its detection performance. First, in the echo spectrum image, the target cell together with the surrounding energy-spillover cells is clustered using a modified image region detector. The decision is then made based on the generalized likelihood ratio test (GLRT) criterion. Theoretical analysis and simulation prove that the algorithm achieves a constant false alarm rate (CFAR). The performance of the proposed detector is assessed by comparison with the single-point GLRT detector and another typical CFAR detector. Monte Carlo simulation results show the superior performance of the proposed detector, which has a higher performance gain, especially in low signal-to-noise ratio (SNR) scenarios. A real-data detection result of a drone swarm further proves the significantly superior detection performance of the proposed detector in the multitarget scenario.