(L + S)-RT-CCD for Terrain Paths Monitoring

In past research, the problem of maritime targets detection and motion parameter estimation has been tackled. This letter aims to contribute to preventing illegal immigration, solving the problem of obtaining reliable paths detection of targets in terms of temporal decorrelation observed on coherent change detection (CCD) maps occurring between two or more complex-valued synthetic aperture radar (SAR) images. Most detection problems are related to terrain clutter and platform motion instabilities which make the paths structure detection and reconnaissance difficult. This letter presents a complete procedure called low-rank plus sparse decomposition radon transform (RT) CCD for automatic estimation and tracking of target paths by evaluating the generated temporal decorrelation CCD-SAR images, observed at the desert environments. The algorithm consists of evaluating a dual-stage low-rank plus sparse decomposition (LRSD) assisted by RT for clutter reduction, sparse object detection, and precise path inclination estimation. The algorithm is based on the robust principal component analysis (RPCA) implemented by convex programming. The LRSD algorithm permits the extrapolation of sparse objects of interest consisting of the incoherent patterns generated by targets from the unchanging low-rank and more coherent background. This dual-stage RPCA and RT applied to SAR-CCD surveillance permits fast detection and enhanced parameter estimation of terrain target paths.