Abstract
Through the coherent accumulation of target echoes, inverse synthetic aperture radar (ISAR) imaging achieves high azimuth resolution. However, because of the instability of the radar system, the echoes of the lSAR will be randomly lost. The conventional FFT processing methods can cause image blur and high sidelobes or other issues. A novel algorithm for ISAR missing-data imaging based on the Iterative Adaptive Approach (IAA) is proposed. The algorithm enjoys global convergence properties and does not need to set the parameters in advance. The missing-data ISAR imaging results for simulated and measured data illustrate the effectiveness of the algorithm.
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