Research Of Moving Target Detection And Parameter Estimation Methods For Multichannel SAR In Complicated Conditions

The combination of synthetic aperture radar(SAR)and ground moving target indi-cation(GMTI)can simultaneously acquire the high-resolution image of the ground scene and achieve detection,velocity estimation and location of the ground moving target,which provides a wide-range and all-weather surveillance of the ground.Due to these proper-ties,the SAR-GMTI technology has a extremely important value in applications such as military reconnaissance,traffic management,region surveillance and so on.Compared to the single-channel SAR-GMTI system,multichannel SAR-GMTI system is able to ef-fectively tackle the complicated environment and provides better overall performance in moving target detection and parameter estimation.However,in real applications,the multichannel SAR-GMTI system confronts three complexities:the complexity of the environment,the complexity of the target motion,and the complexity of the computation,these three complexities are termed as compli-cated condition in this work.The complexity of the environment means that the ground scene may contain several types of land covers and the clutter power changes in a hetero-geneous manner,which makes the space-time adaptive processing(STAP)-based clutter suppression and target detection approaches suffer a performance loss or even fail.The complexity of the target motion means that the target motion is extended from the a single motion form of constant motion to multiple motion forms including acceleration,micro-motion,etc.;if the matched filter used is generated by the parameters of the static target,the mismatch of motion(target defocusing)will be more notable,which makes target de-tection performance decline severely.The complexity of the computation means that in order to tackle the complexities of environment and target motion,and achieve a better performance,the computational efficiency of target detection and parameter estimation approach will be low as they rely on searching,which limits the application of the tech-nique.This dissertation detailedly investigates moving target detection and parameter es-timation methods for multichannel SAR in complicated conditions.Based on the multi-channel SAR signal models,the properties of multiple-forms moving targets are analyzed thoroughly,SAR-GMTI methods with high overall performance and high computational efficiency are developed by fully exploitting the properties of the multichannel SAR sig-nal,and the detection and parameter estimation of multiple-forms moving targets in com-plicated conditions are achieved.This dissertation firstly elaborates the background and the significance of the re-search from the perspectives of the application value,confronting challenge and difficul-ties of the SAR-GMTI technique,summarizes the development history and current work of SAR-GMTI,points out the deficiency of the existing SAR-GMTI methods and parts that need improvement,and introduces the key point of the research according to these.In Chapter 2,the multichannel SAR signals of the clutter and the moving targets are established and their properties are analyzed.The signal models of the clutter,the constant velocity moving target,the acceleration moving target,and micro-motion target in the 2-D time domain,the range-Doppler domain,and the SAR image domain are established;the modulation form of single-channel signal and multichannel interference phase of different targets in different signal domains are analyzed;and more complete signal models of the clutter and the target,analysis conclusions of their properties are achieved,which provides a basis for the following research of the SAR-GMTI methods.Chapter 3 focuses on the detection of constant velocity moving target in the image domain.The block-pixels property of the constant velocity moving target is analyzed,the self matched filter and adaptive self matched filter whose prototypes are the matched filter and adaptive matched filter are developed.The core of these two detection methods is that the multichannel signal of the neighbours of the cell under test can be used as an substitute for the steering vector of the moving target,which removes the searching of the steering vector of the moving target,such that the detection methods have a computa-tional efficiency improvement of multiple tens while maintain the detection performance simultaneously.Chapter 4 aims at the performance loss problem induced by the mismatch of the existing image-domain detection methods and multiple-forms moving targets,proposes the 2-D time domain generalized likelihood ratio test(GLRT)method which is applica-ble to multiple-forms moving targets based on the statistical hypothesis test theory and the multichannel signal models.According to the forms of the detector and the azimuth invariance of the SAR transfer function,the GLRT method is achieved by the 2-D space-time matched filter.Furthermore,to solve the low computational efficiency problem,the 2-D time domain GLRT method is simplified and a two-step detection framework based fast moving target detection method is proposed.The rationale of the two-step detection framework is use the preliminary detection method with high computational efficiency to select range cells that contains the moving targets ans perform the secondary detection method on the detected range cells.The preliminary detection method is based on the bandpass STAP filter,it only performs space filtering and does not include focusing pro-cessing of the target,which can be viewed as the extension of the image-domain STAP detection methods for the constant velocity moving target.Chapter 5 studies the parameter estimation and imaging of the moving target.Firstly,a constant velocity moving target parameter estimation and imaging method based on the synthetic channel signal and the extended range-Doppler domain 1-D matched filter is proposed,which is the equivalent transform of the optimum parameter estimation of the constant velocity moving target.Then,based on the approximation of the signal model,a acceleration moving target parameter estimation and imaging method based on the syn-thetic channel signal and the extended range-Doppler domain 1-D matched filter is pro-posed;compared to the constant velocity moving target parameter estimation and imaging method,the cubic phase coefficient estimation is added.In order to achieve decoupling and estimation of all the parameters of the acceleration moving target,a method for the range velocity and acceleration estimation based on the multichannel signal and the max-imum likelihood method is further proposed.For the micro-motion target,the uniqueness of micro-motion signal in multichannel stripmap SAR radar system is pointed out and a parameter estimation and imaging based on the multichannel signal and the maximum likelihood method is proposed.Chapter 6 summarizes the dissertation and points out the potential directions of the following research.