Using multi-radar signal fusion to fuse multi-angle and multi-band signals can improve the range and cross-range resolution of images. To overcome the limitation of multi-radar signal fusion based on spectral estimation, whose solidity depends heavily on the estimated accuracy of the number of scattering centers and the matching accuracy of two-dimensional poles, a linear representation model of multi-radar signal fusion is constructed. Then the sparsity of inverse synthetic aperture radar (ISAR) signal in the Fourier domain is excavated, and a new multi-radar signal fusion method based on signal sparse representation is proposed in this paper. From the analysis and simulation, it can be seen that the accuracy of parameters estimation based on signal sparse representation is better than that from the spectral estimation, while the operation efficiency of the new method is a little lower. But the performance of parameters estimation of the new method is affected by signal sparisty.
YE Fan, HE Feng, ZHU Jubo, ZHANG Yongsheng
. Multi-radar Signal Two-dimensional Fusion Processing Based on Sparse Representation[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2011
, 32(3)
: 515
-521
.
DOI: CNKI:11-1929/V.20101213.1757.007
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