Unitary ESPRIT Based Multiband Fusion ISAR Imaging
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摘要:
多频带融合成像可有效提高ISAR成像的距离分辨率。传统的ESPRIT谱估计融合算法只利用了复数观测数据本身，而没有利用其共轭数据。该文提出对合成复观测数据及其共轭的酉ESPRIT法进行调整以实现基于酉ESPRIT法的多频带融合ISAR成像。酉ESPRIT法充分利用复数观测数据信息，更有利于多频带融合的频谱估计和ISAR成像。针对多频带融合中目标散射点越分辨单元徙动校正的问题，调整了传统校正处理的步骤，分别在多频带融合前进行越距离单元徙动校正和融合后进行越多普勒单元徙动校正，避免了回波中的快时间频率-慢时间耦合项以及时域相位补偿对频域融合处理的影响，从而得到效果更好的多频带融合ISAR图像。仿真和实测数据结果表明所提方法不但能得到高质量的融合ISAR图像，也具有更优的抗噪性能和更高的运算效率。
Abstract: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.
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