Time-Weighting Symmetric Accumulated Cross-Correlation Method of Parameter Estimation
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Motion compensation based on the parameter estimation of a moving target has a strong influence on the inverse synthetic aperture radar (ISAR) imaging quality. For the target with built-in disturbance components or under an extremely low signal-to-noise ratio (SNR), conventional parameter estimation methods based on cross-correlation processing of adjacent profiles, such as the cross-correlation method and the accumulated cross-correlation method, give sizable aligned errors and subsequently produce low-quality ISAR images. The fractional Fourier transform is capable of concentrating the signal power; however, a large computational complexity is induced by searching the matched order. In view of the problems above, a time-weighting symmetric accumulated cross-correlation method is proposed herein. This method maps the spectrum of the range profile into a single-peak envelope to reduce range alignment errors, and presents a symmetric accumulated manner to offset the accumulated error. The simulation results demonstrate that the proposed method yields much better estimation precision than other methods, and yields extremely low computational complexity.
KeywordsISAR motion compensation parameter estimation time-weighting cross-correlation
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