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The problem of accurately measuring the motion parameters of low radar cross-section (RCS) maneuvering targets has long been a hurdle in the radar technology landscape. Small targets, due to their elusive characteristics, are particularly difficult to detect with conventional radar systems. In this paper, we investigate the capabilities of dechirp-receiving stepped-frequency radar, a modern system using a linear frequency modulation signal for downconversion. This permits the radar to function at reduced sampling rates while maintaining the transmission of large-bandwidth signals and achieving synthetic imaging. Our primary contribution is introducing the stepped dechirp generalized Radon–Fourier transform (stepped DGRFT) algorithm. This novel approach allows the radar system to perform coherent accumulation, enhancing the accuracy of motion parameter estimates for low-RCS maneuvering targets. Results from our simulations and measured data analysis validate the effectiveness of our proposed algorithm, demonstrating its superiority over other methods. [ABSTRACT FROM AUTHOR]

This paper proposed a Pulse-Agile-Phase-Coding slow-time MIMO (PAPC-st-MIMO) waveform, where the phase-coded signal is utilized as the intra-pulse modulation of the slow-time MIMO waveform. Firstly, the signal model of the proposed waveform is derived. To improve the orthogonality of the phase-coded waveform sets, a novel hybrid evolutionary algorithm based on Cyclic Algorithm New (CAN) is proposed. After the optimization process of the phase-coded waveform sets, the signal processing method of the PAPC-st-MIMO waveform is derived. Finally, the effectiveness of the proposed method is verified with a simulation experiment. The mitigation ratio of the near-range detection waveform can achieve −30 dB, while the long-range detection waveform can achieve −35 dB. This approach ensures waveform orthogonality while enabling the slow-time MIMO waveform to achieve distance selectivity. By conducting joint pulse-Doppler processing across multiple range segments, range ambiguity can be suppressed, increasing the system's Pulse Repetition Frequency (PRF) without introducing ambiguity. [ABSTRACT FROM AUTHOR]

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]