Gross error detection and application of ground-based SAR in complex environment

doi:10.13474/j.cnki.11-2246.2020.0042

Abstract

Abstract: The intermittent occlusion of radar line of sight by construction machinery leads to the phase singular value of some images, resulting in unwrapping errors and error transmission, and it is difficult to identify the occluded images by simple related image processing. This paper proposes an improved method of signal singularity detection based on wavelet transform. Through the analysis of the temporal phase characteristics of the ground-based SAR PS points, the occlusion image recognition is transformed into the problem of gross error detection. According to the relationship between the PS point phase sequence and the image position, the occluded image set is obtained according to the singular point set of the PS point phase sequence in the survey area. Finally, the ground-based SAR monitoring results obtained by removing the occluded image are compared and analyzed with the precision total station, level and vernier caliper data. The results show that the method proposed in this paper is feasible for the recognition of occluded images. It solves the problem of gross error in the measurement data caused by the possible image occlusions in the practical engineering application of ground-based SAR, and improves the efficiency and accuracy of the detection of false images in the monitoring area.

Key words: GBSAR, deformation monitoring, gross error detection, wavelet transformation, singularity detection

CLC Number:

P237

MA Jinyu, LONG Sichun, TONG Aixia, WU Wenhao, ZHU Chuanguang. Gross error detection and application of ground-based SAR in complex environment[J]. Bulletin of Surveying and Mapping, 2020, 0(2): 43-48,54.

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