Research On Coherent Integration Methods For Moving Target Detection Based On Moving Radar Platform

Weak moving target detection is one of the important tasks of the radar system.Such targets usually have characteristics of far range,low observation,high speed and high maneuverability,which brings challenges to radar detection.By prolonging the radar observation time,the long-time coherent integration can improve the radar detection performance for weak targets.However,when detecting a ground moving target or an air flying target,an equivalent relative motion state will be generated between the moving platform and the moving target.As the accumulation time increases,the equivalent motion components lead to the linear range migration(LRM),range curvature(RC)and Doppler frequency migration(DFM)of the echo signal,which make the conventional coherent integration algorithms become invalid.In order to detect the moving targets and estimate the motion parameters effectively,this dissertation carries out the studies on the mentioned problems.The main works and contributions of this dissertation are summarized as follows:1.To focus a groud moving target in a uniform moving platform,a fast target detection algorithm is proposed.Firstly,the improved time reversal transform(ITRT)is used to eliminate the RC and DFM in the range-frequency domain.Then,a new Doppler filter bank is designed,and the modified radon Fourier transform(MRFT)is proposed to correct the residual LRM.Finally,the successive coherent integration can be achieved by Doppler filter bank.The proposed method requires only one-dimensional parameter search,and the Doppler filter bank can be implemented by Fast Fourier transform.Therefore,it has low computational complexity.2.As for a groud moving target in a uniform moving platform,a weak target detection and parameter estimation algorithm is proposed,i.e.,modified location rotation transform and improved discrete chirp Fourier transform(MLRT-IDCFT).Firstly,the matched filtering function is constructed to correct the RC.Then,LRM is compensated by MLRT.Finally,a novel IDCFT operator is defined to adaptively adjust the parameter resolution and parameter estimation range,so as to realize the accumulation of signal energy and the estimation of motion parameters.The proposed method can avert the blind speed sidelobe(BSSL)which has good detection performance and parameter estimation performance under the low signal-to-noise ratio(SNR)environment.3.A coherent integration algorithm based on frequency phase compensation function process(FPCFP)is proposed to detect air weak moving targets.By searching the motion parameters,the proposed algorithm constructs a two-dimensional frequency phase compensation function to eliminate the coupling relationship between the slowtime variable and the fast-time variable.As a result,the range migration(RM)and DFM can be corrected.Thereby,the coherent integration is achieved and the motion parameters are estimated.Simulation results show that the proposed algorithm realizes the coherent accumulation of weak targets,which has superior anti-noise performance and parameter estimation performance undert the low SNR environment.Additionally,the proposed algorithm can also effectively handle the multiple moving targets.4.As for a ground maneuvering target in a uniform moving platform,a new target detection and parameter estimation method,based on range frequency reversal transform and searching Lv's distribution(RFRT-SLVD),is proposed.Firstly,according to the symmetrical equal interval sampling of the range frequency,the RM can be eliminated by performing the RFRT operation on the echo signal.Then,the matched filtering function related to the second acceleration is used to compensate the third-order DFM(TDFM).Finally,the signal energy is accumulated and the motion parameters are estimated by LVD.This algorithm can precisely compensate the RM,avoid the BSSL problem and suppress cross terms.