| In Circular Synthetic Aperture Radar(CSAR)imaging process,the detection wave of the Radar always irradiates on the target,and the Radar moves in a circle along the observation center above the observation scene,so that the CSAR system can receive the scattering information of the target 360°.The omni-directional imaging detection of the target is realized.Due to this special imaging method,the azimuth accumulation angle of CSAR system is much larger than that of conventional Linear SAR(LSAR),so CSAR image has higher image resolution and richer scattering information.Theoretically,CSAR image can obtain higher precision target detection results.In terms of concealed target detection in leaf clusters and dense target detection,traditional LSAR imaging detection has disadvantages such as low image signal-to-noise ratio and inability to obtain omni-directional scattering information of the target,which makes it difficult to obtain satisfactory results of concealed target detection and dense target detection.Therefore,the research on target detection algorithm based on CSAR image is of great significance.Combined with engineering practice and application,this paper carried out in-depth research on the detection technology of concealed target and densely parked vehicle target in airborne CSAR image,and achieved some research results of theoretical significance and practical value,which are summarized as follows:1.Based on CSAR imaging geometry and echo signal,the similarities and differences between CSAR and LSAR images are analyzed from two aspects of image speckle characteristics and azimuth scattering characteristics,and the target anisotropy in CSAR images is emphatically studied,which lays a theoretical foundation for the subsequent study of concealed target and dense target detection algorithm of leaf clusters.2.The hidden target detection algorithm of leaf cluster based on CSAR image is studied.Specific work is:(1)using multi-angle observation CSAR image advantage,from different perspectives on the CSAR subaperture images selected reference image and the image to be detected,has solved the traditional SAR targets hidden image change detection problem is difficult to obtain,and accordingly put forward the CSAR image based on region partition is hidden targets change detection method.Compared with the traditional difference change detection method,the detection performance is improved effectively.(2)The difference of the coherence between the target and the trunk clutter in the sub-aperture images is analyzed,and the detection method of the coherence coefficient of concealed target based on the sub-aperture image is proposed,which not only ensures the low false alarm rate,but also preserves the structural characteristics of concealed target as much as possible,and improves the detection performance.3.The dense vehicle target detection algorithm based on CSAR image is studied.The specific work is as follows :(1)aiming at the problem of entanglement of vehicle contours between dense vehicle targets in CSAR image,the segmentation algorithm based on MRF model is proposed to apply to CSAR image to achieve accurate and fast separation of vehicle targets.(2)Aiming at the problem that adjacent vehicle targets cannot be accurately clustered in the scene of dense target observation,a clustering method based on target azimuth estimation is proposed to reduce the clustering error and improve the performance of dense target detection.In this paper,the proposed hidden target detection algorithm and dense vehicle target detection algorithm are applied to the airborne dual-frequency CSAR measured image processing obtained by the research group,which verifies the correctness,effectiveness and practicability of the algorithm,and lays a foundation for further research on the accurate interpretation technology of airborne CSAR image in the future. |
