Study On Moving Target Detection And Parameter Estimation Method With Airborne Multi-channel Radar

Airborne early warning and surveillance radars,which can monitor long-range targets at high-altitude without shielding for a long time,have the advantages of maneuverability and flexibility.Moving Target Indication(MTI)technology adopted by traditional radar is seriously interfered by ground clutter.It is difficult to complete the detection of small targets and moving targets,such as ground armored vehicles,unmanned aerial vehicles,cruise missiles,under the background of strong clutter.The Space-Time Adaptive Processing(STAP)and Synthetic Aperture Radar Ground MTI(SAR-GMTI)are key technologies to solve the problem of moving target detection in the strong clutter background: STAP technology can adaptively generate a notch at the clutter's ridge in space-time two-dimensional plane,so as to obtain good clutter suppression performance;SAR-GMTI technology can suppress clutter and detect moving targets in image domain,and then obtain the motion parameters and positions of ground moving targets.This thesis mainly focuses on the requirements of the airborne multi-channel radar for diversified MTI task,and carries out airborne multi-channel radar MTI from two aspects:(i)STAP-based detection of low-and medium-altitude maneuvering targets;(ii)multi-channel SAR-GMTI-based ground moving target detection and parameter estimation.The main contribution of this thesis includes four parts as follows:1)The general signal model of airborne multi-channel radar for moving target detection is derived.First,by considering the similarities and differences between the airborne multichannel radar STAP and SAR-GMTI processing,this part describes the unified multichannel radar space detection geometric relationship model,beam-pattern model,and derives the basic echo model of moving targets and stationary targets.2)For the airborne multi-channel radar based on STAP technology,the maneuvering target with acceleration at low-and medium-altitudes will cause the response distortion problem of the space-time two-dimensional adaptive filter and the steering vector mismatch problem.Therefore,an adaptive matched filtering method based on an extended direction vector and a discrete searching method for acceleration parameter is proposed.Experimental results show that the response of the adaptive filter using the proposed method focuses well even if the target has a significant acceleration.And the fast estimation of motion parameters is implemented with less computational complexity.3)The performance of multi-channel radar system based on Along Track Interferometric SAR(ATI-SAR)will suffer serious performance loss when performing GMTI task under the condition of non-ideal factors and strong clutter.Therefore,a method based on improved Robust Principal Component Analysis(RPCA)pre-detection and Magnitude & Phase(M&P)post-detection is proposed to realize better detection for moving targets.Compared with the traditional RPCA method,the proposed method can effectively reduce the computational complexity through matrix decomposition,and at the same time,it can expand the selection range of hyperparameter without increasing the false alarm rate.Experimental results show that the proposed method can effectively improve target detection performance and realize good robustness and engineering applicability.4)Due to the difficulty in obtaining effective baseline of the multi-channel radar,the performance of target motion parameter estimation for ATI-SAR system is seriously deteriorated,especially for the existence of airborne yaw motion and low signal-to-noise ratio condition.To solve these problems,an effective baseline estimation method is proposed.After the cross-track error correction and the M&P target detection,the wavelet mean median(WMM)filtering method is proposed to improve the effective baseline estimation accuracy.The effective baseline is then used to estimate the target motion parameters.Experimental results show that the proposed method,compared with traditional methods,improves the accuracy of effective baseline and motion parameter estimation.In addition,the proposed method achieves focused imaging and accurate relocation of moving targets.