Low-slow-small target detection using stepped-frequency signals in a strong folded clutter environment

The popularisation of unmanned aerial vehicles (UAVs) and the security threats that follow have made the detection of low-slow-small (LSS) targets a hotspot in the radar field. For ground-based surveillance radars (GSR), the folded-clutter is an important factor affecting LSS target detection performance. Herein, the stepped-frequency (SF) signal is used to improve the performance of the folded-clutter suppression and the LSS target detection for the GSR. Furthermore, an optimisation method for the SF signal parameter design is proposed to maximise the folded-clutter improvement factor. Specifically, signal parameters including the frequency step number and the step sequence are optimised based on the clutter cognition results. To verify the effectiveness of the well-designed SF signals in the LSS target detection, simulation experiments and field tests using an L-band SF-GSR and a DJI M600-Pro UAV are conducted. Compared to the results achieved by a simple chirp signal, the detection probabilities of the LSS target with different velocities are significantly increased when the SF signals are used in a typical strong folded-clutter background.