High resolution range profile of compressive sensing radar with low computational complexity


On the basis of compressive sensing radar, this study presents a replacement methodology of reconstructing the moving target's high-resolution range profile (HRRP) with low computational complexity. With regard to the spatial sparsity of the radar scene, solely some sub-pulses of frequency-stepped chirp signal (FSCS) are used to sample the target's frequency responses. To scale back the computational complexity of ancient compressive sensing (CS) algorithm which uses FSCS to reconstruct moving target's HRRP, a dynamically deduced sensing matrix is established primarily based heading in the right direction's velocity estimation. Besides, the orthogonality of the deduced sensing matrix is analysed from the angle of FSCS frequency encoding sorts to enhance the HRRP construction accuracy using CS algorithms. Numerical simulations demonstrate that the proposed method performs better than traditional algorithm with smaller estimation error and higher robustness against noise.

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