ISAR imaging of targets with fast rotating parts using adaptive joint time-frequency processing

Based on the adaptive joint time-frequency processing techniques, a new methodology is proposed in this paper to separate the interference due to fast rotating parts from the original ISAR image of the target. The technique entails adaptively searching for the linear chirp bases which best represent the time-frequency behavior of the signal and fully parameterizing the signal with these basis functional. The signal components due to the fast rotating part are considered to be associated with those chirp bases having large displacement and slope parameters, while the signal components due to the target body motion are represented by those chirp bases which have relatively small displacement and slope parameters. By sorting these chirp bases according to their slopes and displacements, the scattering due to the fast rotating part can be separated form that due to the target body. Consequently, the image artifacts overlapping with the original image of the target can be well removed and a clean ISAR image can be produced. Successful applications of the algorithm to numerically simulated and measurement data show the robustness of the algorithm.