Long-time Integration for Drone targets Detection Based on Digital Ubiquitous Radar

“Low (low altitude), slow (slow maneuvering) and small (small size)” targets such as drones pose a serious threat to airport flight safety and urban security, and there is an urgent need for effective detection. These targets have weak echoes and inconspicuous features, covered by strong clutter. Conventional radar data update rates are low with limited integration pulses, making detection extremely difficult. In this paper, the digital ubiquitous radar is used for long-time observation in order to improve the detection performance, and the high-order motion characteristics of low-altitude drone target are analyzed. The long-time integration method is proposed via Keystone transform (KT) and the enhanced fractional Fourier transform (EFRFT) to compensate the range and Doppler migrations simultaneously. Both simulation and real experiment using L-band digital ubiquitous radar are carried out to verify the performance of the proposed method. It is shown that the integration ability is better and the peak spectrum are more obvious compared with the traditional FFT-based moving target detection (MTD) and popular FRFT method.