Study Of Data Reconstruction Method On The SAR With Continuous PRF Variation

Synthetic aperture radar(SAR)is an advanced remote sensing technique,capable of acquiring high resolution images of the Earth's surface independent of weather conditions and sunlight illumination.This makes SAR very attractive for the systematic observation of dynamic processes on the Earth's surface.However,conventional SAR systems are limited in that a wide swath can only be achieved at the expense of a degraded azimuth resolution.In order to solve this contradiction,in recent years,the researchers proposed a variable pulse repetition frequency(PRF)SAR.The system radar uses the Digital Beam-forming(DBF)technique and the parabolic reflector antenna to obtain the SAR image of the high resolution wide swath,and uses the variable PRF to solve the “blind ranges” of the traditional SAR based on DBF technology.So it is of great significance for the study of variable PRF SAR.For the variable PRF SAR,the specific work of this paper is as follows:1.Firstly,the contradiction between high resolution and wide swath is introduced,and the concept of variable PRF SAR is introduced.Then the blind distribution formula of variable PRF SAR is deduced.Considering the error of the echo modeling under the hypothesis,a method of echo modeling under the assumption of non-stop is introduced.Finally,the difficulties of variable PRF SAR target processing are analyzed.2.In this paper,we study the problem of two kinds of variable PRF SAR echoes for low oversampling and continuous loss of pulses.Aiming at the variable PRF SAR echo under low oversampling,we introduce a missing data iterative adaptive algorithm(MIAA)method is introduced.Then,the MIAA method is used to deal with the process of variable PRF SAR.Finally,the effectiveness of MIAA method for variable PRF SAR signal processing under low oversampling is verified by simulation experiments.For the variable PRF SAR echo under continuous loss of pulses,a gapped-data amplitude and phase estimation(GAPES)method is proposed.The same procedure as the MIAA method is introduced,and derived from the formula of GAPES,finally,the effectiveness of the GAPES method for variable PRF SAR signal processing under continuous pulse loss is verified by simulation experiments.3.Aiming at the model of variable PRF SAR data loss,this paper introduces a variable PRF SAR signal processing method based on compression perception.This paper introduces the compression perception theory from three aspects: sparse representation of signal,observation matrix and signal reconstruction.Considering the loss of variable PRF SAR data,the compression sensing processing method of variable PRF SAR is introduced from three aspects: variable PRF SAR compression sensing model,variable PRF SAR azimuth range sampling and signal reconstruction.Finally,the effectiveness of the compression sensing method is verified by simulation experiments.