Abstract
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.
Highlights
For the first question, the subband signals are derived from different wideband radars, and the coherent between them cannot be well guaranteed even though high precision synchronization techniques are adopted[12,13]
In ref. 9, Tian proposed a novel method to estimate the incoherent parameters (ICP), the phase variety caused by the vacant band is not taken into considered, the poles estimated by the root-MUSIC method is affected by the noise, both of them would result in loss of precision
The frequency depend factor (FDF) and the relative ranges relate to the reference range are − 1,1,− 0.5 and
Summary
The subband signals are derived from different wideband radars, and the coherent between them cannot be well guaranteed even though high precision synchronization techniques are adopted[12,13]. 11, a modified root-MUSIC and least square algorithm are used to construct DE model of each subband signal Depending on these models, each subband is extrapolated to get full band signals, high dimension optimization is applied to find the fixed phase and the linear phase. 14, the similarity between high range resolution profile (HRRP) of the subband is utilized to estimate the linear phase, and a cost function is defined to derive the fixed phase. This method has high calculate efficiency, but the estimation precision is related to the sample number. Extrapolation error does not exist here, and the calculation burden is reduced
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