TY - JOUR A2 - Cheney, Margaret AU - Li, Min AU - Zhou, Gongjian AU - Zhao, Bin AU - Quan, Taifan PY - 2014 DA - 2014/03/17 TI - Sparse Representation Denoising for Radar High Resolution Range Profiling SP - 875895 VL - 2014 AB - Radar high resolution range profile has attracted considerable attention in radar automatic target recognition. In practice, radar return is usually contaminated by noise, which results in profile distortion and recognition performance degradation. To deal with this problem, in this paper, a novel denoising method based on sparse representation is proposed to remove the Gaussian white additive noise. The return is sparsely described in the Fourier redundant dictionary and the denoising problem is described as a sparse representation model. Noise level of the return, which is crucial to the denoising performance but often unknown, is estimated by performing subspace method on the sliding subsequence correlation matrix. Sliding window process enables noise level estimation using only one observation sequence, not only guaranteeing estimation efficiency but also avoiding the influence of profile time-shift sensitivity. Experimental results show that the proposed method can effectively improve the signal-to-noise ratio of the return, leading to a high-quality profile. SN - 1687-5869 UR - https://doi.org/10.1155/2014/875895 DO - 10.1155/2014/875895 JF - International Journal of Antennas and Propagation PB - Hindawi Publishing Corporation KW - ER -