Research On Imaging Methods For Distributed Passive Radar Systems

Distributed passive radar imaging mainly refers to a kind of imaging method that can make use of transmitter and receiver for target observation at the same time. The transmitter and receives are distributed on spatial domain. It is emphasized the spatial extensibility of the transmitter and receives to the target. Distributed passive radar imaging problems were analysised from the angles of froward and reverse respectively. Through positive analysis, this paper studies the imaging method based on non-uniform Fourier transform. Through reverse analysis, the method of imaging based on regularization was studied. After combing the sparse prior of target, imaging method based on compressive sensing is studied, and the performance of the method are analyzed and optimized, and the mismatch problem of imaging equation was studied.First of all, distributed passive radar imaging model is established in this article from the perspective of the signal and the geometry. The imaging model shows the Fourier transform relationship between the target scattering coefficient and the echo data in spatial spectrum. The distributed passive radar imaging performance is analyzed in the perspective of spatial spectrum. The relationship between the spatial spectrum filling and the station layout is studied. Study and put forward the distributed passive radar imaging method based on the non-uniform Fourier transform, and analyzes the performance of the method through the simulation, the research shows that the method can get a good imaging results in the uniform and dense space spectrum filling condition.This article study the distributed passive radar imaging problem from the perspective of inverse problem in more general condition. This paper suggests that imaging inverse problem is essentially an ill-posed problem. Analyzed the imaging characteristics of inverse ill-posed problem, and presents a general law between the ill degree and the station layout. Study and put forward a distributed passive radar imaging based on Tikhonov regularization method to weaken the influence of the ill-posed problem. A distributed passive radar imaging method based on truncated total least squares is proposed in order to weaken the system disturbance in reconstruction matrix. The imaging performance is analyzed and compared through the simulation.The distributed passive radar imaging problem based on compressive sensing is studied for the station number is limited in the actual environment, and the corresponding spatial spectrum filling in a state of sparse. Several classical algorithm was applied to imaging inversion. The reconstruction characters of orthogonal matching pursuit algorithm under the condition of noise carried on the research. The iterative parameter values and the probability of successful reconstruction is derived. The station layout optimization problem is studied under the condition of sparse imaging. The optimization performance is analyzed and compared through the simulation.Finally, two class reconstruction matrix mismatch problem in the sparse distributed passive radar imaging problem is studied respectively. The influence of position error on imaging process is studied based on the imaging model containing position error. The position error estimation and correction method based on auxiliary scattering point is proposed for the mismatch problem caused by position error. This paper proposes a direct solving scattering point location method based on spectrum estimation technique for mismatch problem caused by Off-Grid, and is verified by simulation.