Application of adaptive joint time-frequency processing to ISAR image enhancement and Doppler feature extraction for targets with rotating parts

A new methodology based on adaptive joint time-frequency processing is proposed 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 functions. 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 having 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 from that due to the target body. Consequently, the image artifacts overlapping with the original image of the target can be removed and a clean ISAR image can be produced. Furthermore, useful rotation rate information contained in the Doppler signal can be extracted. Successful applications of the algorithm to numerically simulated and measurement data show the robustness of the algorithm.