NDLI: MIMO Radar 3D Imaging Based on Combined Amplitude and Total Variation Cost Function With Sequential Order One Negative Exponential Form

Content Provider	IEEE Xplore Digital Library
Author	Changzheng Ma Tat Soon Yeo Yongbo Zhao Junjie Feng
Copyright Year	1992
Abstract	In inverse synthetic aperture radar (ISAR) imaging, a target is usually regarded as consist of a few strong (specular) scatterers and the distribution of these strong scatterers is sparse in the imaging volume. In this paper, we propose to incorporate the sparse signal recovery method in 3D multiple-input multiple-output radar imaging algorithm. Sequential order one negative exponential (SOONE) function, which forms homotopy between ℓ₁ and ℓ₀ norms, is proposed to measure the sparsity. Gradient projection is used to solve a constrained nonconvex SOONE function minimization problem and recover the sparse signal. However, while the gradient projection method is computationally simple, it is not robust when a matrix in the algorithm is ill conditioned. We thus further propose using diagonal loading and singular value decomposition methods to improve the robustness of the algorithm. In order to handle targets with large flat surfaces, a combined amplitude and total-variation objective function is also proposed to regularize the shapes of the flat surfaces. Simulation results show that the proposed gradient projection of SOONE function method is better than orthogonal matching pursuit, CoSaMp, ℓ₁-magic, Bayesian method with Laplace prior, smoothed ℓ₀ method, and ℓ₁-ℓ_s in high SNR cases for recovery of ±1 random spikes sparse signal. The quality of the simulated 3D images and real data ISAR images obtained using the new method is better than that of the conventional correlation method and minimum ℓ₂ norm method, and competitive to the aforementioned sparse signal recovery algorithms.
Sponsorship	IEEE Signal Processing Society
Starting Page	2168
Ending Page	2183
Page Count	16
File Size	12783980
File Format	PDF
ISSN	10577149
Volume Number	23
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Imaging Radar imaging MIMO radar Matching pursuit algorithms Vectors Receiving antennas combined amplitude and total-variation 3D imaging sparse signal recovery sequential order one negative exponential function SVD diagonal loading
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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