Low-observable target detection using two-stage RFRFT

Long-time coherent integration is an effective method to implement low-observable target detection in a complex scenario. Radon-fractional Fourier transform (RFRFT) can compensate the range and Doppler migration simultaneously and obviously improve the signal-to-clutter-noise ratio (SCNR) via long-time coherent integration. However, RFRFT uses a combination of moving parameters, i.e. initial range, velocity and acceleration, to search targets, increasing the computational burden. In this study, a novel two-stage RFRFT is proposed to detect low-observable targets. In the first stage, by calculating the spectrum similarity between adjacent bins, regions of interest (ROIs) can be detected in the range–Doppler domain. The processing in the first stage reduces the global search to a limited number of ROIs. In the second stage, based on the extraction of moving parameters, a refined search is performed to realise target detection and false alarm discrimination. To verify the effectiveness of the proposed two-stage method, both a simulation scenario and real radar dataset are applied. The theoretical analysis and experiment results show that the novel method is effective for the detection of dim targets with far less computation than standard RFRFT.