基于酉ESPRIT的多频带融合ISAR成像

Multiband fusion imaging can effectively improve the range resolution of Inverse Synthetic Aperture Radar (ISAR) imaging. The traditional Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) spectral estimation signal fusion algorithm uses only the complex measured data without using their conjugate data. This paper proposes to modify the unitary ESPRIT method, which is based on synthesizing complex observation data and its conjugate data, to achieve unitary ESPRIT based multiband fusion ISAR imaging. The unitary ESPRIT method makes full use of the information of complex observations, which is more beneficial to multiband frequency spectrum estimation and ISAR imaging. Furthermore, for the correction of Migration Through Resolution Cell (MTRC) of scatterers in multiband fusion, the traditional processing flow is adjusted and optimized. The migration through range cell correction and the migration through Doppler cell correction are performed before and after the multiband fusion respectively, which avoids the influence of the fast time frequency - slow time coupling in the echo and the phase compensation on the spectrum fusion processing, thereby a better multiband fusion ISAR image is obtained. Simulation and real data experimental results show that the proposed methods can not only get high quality ISAR images, but also have good antinoise performance and higher computational efficiency.