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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. [ABSTRACT FROM AUTHOR]

The latest progress of the multiple‐input multiple‐output (MIMO) radar system developed for small drones detection at Beijing Institute of Technology is presented herein. A low‐cost S‐band MIMO scanning radar system is designed for the detection of small drones. A practical design optimisation and implementation of a sparse array covering the whole airspace, and a target‐based MIMO radar array calibration method to improve the signal‐to‐noise ratio of the target are proposed. An experiment in the microwave chamber was conducted to verify the designed sparse‐array beam‐pattern, and measurement campaigns for small drones were performed to test the system performance where the radar achieved detection and tracking of a small DJI‐Phantom 4 drone at a range of up to 5 km. Target features, including micro‐Doppler and radar cross‐section signatures were extracted to assist target classification. The experimental results indicate that the system has promising capability in small drones detection and tracking, despite the challenges of low dwell time on targets due to the scanning nature of the system. [ABSTRACT FROM AUTHOR]