A symmetric accumulated cross-correlation method of parameter estimation based on fractional fourier transform for ISAR motion compensation

Motion compensation (MOCOMP) based on parameter estimation of the target directly affects the quality of ISAR imaging. In poor noise environment, conventional parameter estimation methods based on cross-correlation processing of adjacent profiles give sizable aligned error. Because envelopes of range profiles produced by the traditional Fourier transform are much more tanglesome in this case. As the echo signal sampled in fast time can be approximated as the combination of multiple Chirp signals with a same Chirp rate, a symmetric accumulated cross-correlation method based on FrFT range compression (Fr-SACCM) is proposed in this paper. It maps the spectrum of the Chirp signal into a single-peaked envelope to reduce the range alignment error, and puts forward a symmetric accumulated manner to offset the accumulated phase error. Meanwhile, the proposed method conducts an optimized iterative searching scheme for the FrFT matched-order and reduces the computational complexity substantially. Compared with other methods, the proposed method has much better performance. Simulation results demonstrate its effectiveness.