Journal Article10.1109/JSEN.2016.2604046
Parametric Sparse Representation Method for Motion Parameter Estimation of Ground Moving Target
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TL;DR: In order to reduce the amount of echo data and achieve a wider observation swath, a parametric sparse representation method for the motion parameter estimation of ground moving targets is proposed with low pulse repetition frequency (PRF).
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Abstract: In order to reduce the amount of echo data and achieve a wider observation swath, a parametric sparse representation method for the motion parameter estimation of ground moving targets is proposed with low pulse repetition frequency (PRF). First, the displaced phase center antenna technique is introduced to cancel the clutters. Second, since range cell migration is not subject to PRF limitations, Hough transform is adopted to estimate the across-track velocities and range positions of moving targets. Then, the parametric method is put forward to estimate the along-track velocities and azimuth positions based on the parametric over-complete chirplet basis matrix, where the basis matrix is determined by the along-track velocities of moving targets. The proposed algorithm can adaptively refine the basis matrix to achieve the optimal sparse representation result. Meanwhile, the azimuth position is obtained by the optimal sparse representation result. Finally, the feasibility and the effectiveness of the proposed method are proved by the simulation results.
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Citations
Omega-KA-Net: A SAR Ground Moving Target Imaging Network Based on Trainable Omega-K Algorithm and Sparse Optimization
TL;DR: The proposed trainable Omega-KA network (Omega-KA-net) forms a new GMT imaging method that can be applied to high-quality imaging under down-sampling and a low signal to noise ratio (SNR) while saving the imaging time substantially.
Low-Altitude and Slow-Speed Small Target Detection Based on Spectrum Zoom Processing
TL;DR: Through the theoretical analysis and real data verification, it is shown that the proposed algorithm can obtain a preferable spectrum zoom result and improve the signal-to-clutter ratio (SCR) with a very low computational load.
Sparse SAR Imaging Method for Ground Moving Target via GMTSI-Net
TL;DR: The proposed imaging network can achieve faster and more accurate SAR images of ground moving targets under a low sampling ratio and signal-to-noise ratio (SNR) and improve the adaptability of the network to the input of echo data with different sampling ratios.
Optimal Coherent Processing Interval Selection for Aerial Maneuvering Target Imaging Using Tracking Information
TL;DR: This article focuses on selecting optimal CPI for ISAR imaging of maneuvering targets, and a novel method using tracking information is proposed that provides robust performance.
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Rotational Angular Velocity Estimation of Rotor Target via 3D-OMP-Based Parametric Sparse Representation
TL;DR: In this article, a rotational angular velocity estimation method is proposed based on complex empirical mode decomposition (CEMD) and three-dimensional orthogonal matching pursuit (3D-OMP)-based parametric sparse representation (PSR) technique.
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Joel A. Tropp,Anna C. Gilbert +1 more
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