Research On High Speed Target Detection Algorithm Based On Sparse Fourier Transform

With the rapid development of the radar field,the scale of data that needs to be processed in real time is increasing,and the fast Fourier transform-based high-speed target detection method has a large amount of calculations and cannot meet the radar target detection real-time requirements.Sparse Fourier transform is a fast algorithm that utilizes the sparsity of signal frequency domain.This algorithm greatly improves the signal processing speed and opens up new directions for rapid data processing.Firstly the paper analyzes the factors affecting radar echoes and establishes the echo model of high-speed targets.The influencing factors of high-speed target detection are studied and mathematical derivation and simulation analysis are performed.The uniform high-velocity target is taken as object,the reason of the distance walking is analyzed,and the structure of the distance walking compensation algorithm is proposed.The keystone transform based on time domain compensation and the envelope interpolation shift based on frequency domain compensation are introduced respectively for the structure of the proposed compensation algorithm.Bit compensation algorithm.Secondly,the basic theory of sparse Fourier transform is introduced and the SFFT algorithm is applied to the common target detection based on sinusoidal signals.The conditions of applying SFFT,and the influence of filter parameters and the length of sub-basket on detection performance are discussed.The feasibility of the sinusoidal signal detection algorithm based on SFFT is proved by simulation,and it is pointed out that the effectiveness of the target detection can only be ensured by selecting the appropriate filter parameters and segment length.Finally,the SFFT-based sinusoidal signal detection and high-speed target detection algorithms are extended to the SFFT-based high-speed target detection algorithm,which is the algorithm in this paper.For the problem of distance walking in high-speed target detection,the proposed algorithm first performs speed compensation after SFFT is divided into baskets,and then performs MTD operation.Finally,the target position and speed parameters are estimated.Through the simulation and verification of the algorithm and from the perspective of detection performance and computational complexity,the proposed algorithm is compared with the currently popular Keystone algorithm and envelope interpolation shift compensation algorithm.The results show that the proposed algorithm has better target detection performance and computational complexity.Low,improves the real-time performance of high-speed target detection.