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A Matrix Pencil Algorithm Based Multiband Iterative Fusion Imaging Method

机译:基于矩阵铅笔算法的多频带迭代融合成像方法

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摘要

Multiband signal fusion technique is a practicable and efficient way to improve the range resolution of ISAR image. The classical fusion method estimates the poles of each subband signal by the root-MUSIC method, and some good results were get in several experiments. However, this method is fragile in noise for the proper poles could not easy to get in low signal to noise ratio (SNR). In order to eliminate the influence of noise, this paper propose a matrix pencil algorithm based method to estimate the multiband signal poles. And to deal with mutual incoherent between subband signals, the incoherent parameters (ICP) are predicted through the relation of corresponding poles of each subband. Then, an iterative algorithm which aimed to minimize the 2-norm of signal difference is introduced to reduce signal fusion error. Applications to simulate dada verify that the proposed method get better fusion results at low SNR.
机译:多频带信号融合技术是一种提高ISAR图像距离分辨率的实用有效的方法。经典融合方法通过根-MUSIC方法估计每个子带信号的极点,并且在几次实验中都获得了一些良好的结果。但是,这种方法在噪声方面很脆弱,因为适当的极点很难获得低信噪比(SNR)。为了消除噪声的影响,提出了一种基于矩阵铅笔算法的多频带信号极点估计方法。并且为了处理子带信号之间的相互不相干,通过每个子带的对应极点的关系来预测不相干参数(ICP)。然后,引入了旨在最小化信号差的2-范数的迭代算法,以减少信号融合误差。模拟dada的应用证明,该方法在低SNR时可获得更好的融合效果。

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