Abstract
Inverse synthetic aperture radar (ISAR) uses target's motion to generate images on the range- Doppler plane. The conventional ISAR uses Fourier transform to compute Doppler spectrum for each range cell. Due to the target irregular translational and rotational motion, the Doppler frequency in fact is time-varying. By using Fourier transform, the reconstructed image becomes blurred. To represent time-varying Doppler spectrum, time-frequency transform should be utilized. Adaptive time-frequency wavelet transform is a very useful tool in analysis of signals with time-varying spectrum. We applied adaptive time-frequency wavelet transform to ISAR image reconstruction and developed a simulation procedure to describe the characteristics of the algorithm. By replacing the conventional Fourier processor with the adaptive wavelet processor, a 2D range-Doppler Fourier ISAR frame becomes a 3D time- range-Doppler wavelet ISAR cube. By sampling in time, a time sequence of 2D range-Doppler images can be viewed. Each individual wavelet ISAR image provides not only superior resolution but also the temporal information within each frame time. Both simulated and real ISAR data have been tested. The result from simulated ISAR data is illustrated in this paper.
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