Ship identification in sequential ISAR imagery
Abstract: We have developed an online system that automatically identifies ships observed in a rapidly updating sequence of range-Doppler images produced by inverse synthetic aperture radar (ISAR). In the system, in order to cope with the invariable noise due to the physics of imaging, we propose to employ a multiframe image processing algorithm that stably extracts profiling as a basic feature reflecting all characteristics of a target. For ship identification, representing the extracted profiles as high-dimensional vectors, we adapt the vector analysis using the recently proposed constrained mutual subspace method (CMSM). The system currently works on an ordinary PC at 5 frames/s and achieves feasible performance of identification. The system is verified using simulated data.
Loading