Parameters estimation and ISAR imaging of multiple maneuvering targets based on an order reduction method for cubic chirps

Inverse synthetic aperture radar (ISAR) imaging is an efficient method for providing high resolution image of maneuvering target especially in many military applications. Practically, the received echoes of complex maneuvering target are always described as cubic phase signals (CPS). Then, migrations through resolution cells are inevitably induced. Additionally, for scenes in which multiple targets exist, the situations become even worse. In this paper, an algorithm for parameters estimation and ISAR imaging of multiple maneuvering targets is proposed, where adjacent cross correlation function (ACCF), modified keystone transform (MKT), fractional Fourier transform (FrFT) and Hough transform (HT) are employed. The algorithm firstly employs ACCF to obtain a reduced order of the original CPS. Then, MKT and FrFT are introduced to realize parameters estimation of multiple targets. Thirdly, motion compensations for each target are accomplished with the estimators. Noting that the radar echoes are not separated previously, compensation result for one target is certainly interfered by the signal components of the others. To resolve this problem, edge detection and HT are utilized to separate the corrected range profile history. Finally, focused ISAR images of each target are obtained after azimuth compression. Simulation results demonstrate the validity of the proposed algorithm.