Signal Integration and Detection Method for Radar Moving Target With Unknown Time Information

Two primary challenges exist in moving target detection and estimation using long-term integration. First, the target velocity would cause range walk (RW). Second, the time information of target entry or departure radar beam usually unknown. These problems would cause severely impact for target detection and parameters estimation. To address signal integration and detection of moving targets with unknown time information, a coherent integration and estimation method named Normalization Window Radon Fourier Transform (NWRFT) is proposed. The method achieves target focusing and estimation through parameters search, and the optimality is also proved based on maximum likelihood. Besides, considering the computational cost of NWRFT, we propose a sub-optimal method based on Radon Fourier Transform and Normalization Window Fourier Transform (RFT-NWFT), using dimension reduction to maintain an optimal balance between integration efficiency and computational burden. In particular, the velocity estimation and range coarse estimation of target are obtained by Radon Fourier Transform (RFT), then the echo signal is retrieved using the estimated parameters. Subsequently, the extracted signal is processing through Normalization Window Fourier Transform (NWFT) to obtain the time information estimation. Experiments using both simulated and real radar datasets demonstrate the effectiveness of NWRFT and RFT-NWFT.