UAV target detection and parameter estimation in non-homogeneous clutter

Abstract

Aiming at the problem of UAV target detection and parameter estimation in non-homogeneous clutter with STLFMCW radar, a SK-CFAR detector is proposed based on the local spectrum refinement. By using zoom-FFT, the two-dimensional spectrum of the received signal is extracted for local template matching. Subsequently, the two-dimensional SK-CFAR detector and CLEAN technique are applied to decide whether there exist some targets in the region of interest. Compared with Radon–Fourier transform (RFT) and moving target detection (MTD), the proposed estimator based on local speed compensation is a good choice for the trade-off of high performance and low computational load even though the input signal-to-clutter ratio approaches to −24 dB.

Keywords

• radar clutter
• parameter estimation
• radon transforms
• fast fourier transforms
• object detection
• signal detection
• radar detection
• fourier transforms
• cw radar
• fm radar
• correlation methods
• target tracking
• uav target detection
• parameter estimation
• nonhomogeneous clutter
• stlfmcw radar
• sk-cfar detector
• local spectrum refinement
• zoom-fft
• two-dimensional spectrum
• local template matching
• local speed compensation
• input signal-to-clutter ratio
• noise figure -24.0 db