Multi-band Radar Signal Fusion based on GTD Model

摘要

Multi-band radar signal fusion can improve rangernresolution of range profile. The performance of fusionrnbased on spectrum estimation is limited by estimationrnof scattering model order. Furthermore, owing tornsparse distribution of multi-band, the mutualrncoherence of observation system matrix is destroyed,rnand the global optimal solution of Basis Pursuitrn(sparse representation on based on l1 -norm) is unequal tornreal sparse representation of signal. Thus a method ofrnfusion based on sparse Bayesian learning is proposedrnin this paper. This method avoids estimation of modelrnorder, and overcomes the limitation of Basis Pursuit.rnThe experimental results also show the advantage ofrnthis method.