Synthetic Aperture Radar Imaging Algorithm For Phase Noise Mitigation

Synthetic Aperture Radar(SAR)is a high-resolution microwave imaging radar.SAR utilizes microwave remote sensing technology to provide all-weather and all-day information of a target.Since the advent,SAR has become an indispensable means of remote sensing information technology.After nearly half a century of rapid development,SAR has been widely used not only for military purposes but also for non-military purposes.Since SAR is a coherent imaging system,therefore it is sensitive to the phase information in the echo signal.And the quality of SAR reconstruction images will be easily interfered by the phase noise in SAR echos.The random phase noise will cause serious defocus in SAR reconstruction images.The applications for both the military purposes and the non-military purposes have urgent needs and great expectations of phase noise mitigation in SAR imaging.In order to improve the quality of SAR reconstruction image and make it more conducive to target feature extraction and target recognition,the paper studies the phase noise mitigation and imaging algorithm of spotlight SAR.The main work is as follows:Firstly,the causes of random phase noise in SAR imaging and the influence of random phase noise on SAR images are studied.The working mode of the spotlight SAR with random phase noise is analyzed.Based on these,the detection model of the spotlight SAR and the theoretical model of spotlight SAR imaging are obtained.Secondely,aiming at the problem that the space limitation of ground-based SAR in airport runway environment,we propose a new system of cantilever arc spotlight SAR detection system and establish the geometric model and echo model of RAAS-SAR system.This paper analyzes and deduces the RASS-SAR imaging model with phase noise interference and proposes a QCS autofocus algorithm based on sparse priori hypothesis of target space.Moreover,this paper proposes a block-based BBQCS fast reconstruction autofocus algorithm.This algorithm based on the idea of blocking can greatly reduce the computational complexity of the algorithm and has the potential of parallel computing.Finally,this paper propose a minimum-based SAR phase noise mitigation and imaging algorithm.Under the minimum phase criterion,this paper poposes a SAR phase noise mitigation and imaging algorithm to overcome the problem that the the sparseness parameter of the target scene is usually unknown in practice.This algorithm reformulates the original non-convex quadratic reconstruction problem into a convex quadratic programming problem.Then,under tht minimum criterion,the algorithm using the Alternating Direction Method of Multipliers(ADMM)and Kolmogorov Spectal Factorization(KoSF)to mitigate the phase noise and get a SAR reconstruction image.The algorithm takes advantage of the structural advantages of quadratic measurement,and the algorithm does not need to introduce sparse prior condition,so the algorithm has better noise robustness.