| Synthetic Aperture Radar (SAR) plays an important role in civilization and militaryapplications with the advantage of all-weather, full-time, long-range, wide-field andhigh-resolution for targets detection and relocation. Ground moving target indication is ahot topic in SAR research and a basic function of SAR. Ground moving target contains awealth of information, moving target detection and parameter estimation has importantpractical significance. This thesis mainly studies the topic of moving targets detectionand parameters estimation for single channel SAR based on compressed sensing method.The major contents and innovation of this thesis is as follows:Firstly, introduces the principle of SAR imaging,development and application ofmoving target detection and Compressed Sensing, then propose a approach to detect roadinformation, moving target and rotational target based on compressed sensing.Secondly, a method of moving target indication in single SAR imagery is proposed.First, a road detection method based on compressive sensing for single SAR image ispresented in this paper, the fuzzy C mean method is used to classify the SAR imageaccording to the road characteristics of the SAR images, and the road pixels are extracted,then shows how compressive sensing can be used to find lines in images, by exploitingsparseness in the Hough transform domain. Secondly, detect the moving targets by a newindication method based on sparse representation. In SAR image, different velocities ofmoving target lead to different defocuses and range cell migration. Based on thischaracter, the over-complete dictionary of targets sample images with different speeds isconstructed. Then the test SAR images are blocked into sub-images and thecorresponding coefficients are calculated with the dictionary. According to thecoefficients, moving target can be detected and the motion parameters can be estimated.Finally, eliminate the effects of Doppler ambiguity on motion parameters estimation,exclude the false target and calibrate motion parameters.Finally, analyzes the echo of rotational target and effects of rotational targets on theconventional SAR images in detail, construct the over-complete dictionary based on its character. Then judge the rotational target exist in SAR image using exploitingsparseness in the Hough transform domain. exclude the false target by motioncompensation. |
