compress sensing
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2019 ◽  
Vol 24 (4) ◽  
pp. 719-724
Author(s):  
Seongho Kim ◽  
Sejong Yoo ◽  
Mincheol Jeon ◽  
Jinseo Park ◽  
Soonyong Kwon ◽  
...  

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 874
Author(s):  
Lin Shi ◽  
Xiaoxiu Zhu ◽  
Chaoxuan Shang ◽  
Baofeng Guo ◽  
Juntao Ma ◽  
...  

Due to the large size of space targets, migration through resolution cells (MTRC) are induced by a rotational motion in high-resolution bistatic inverse synthetic aperture radar (Bi-ISAR) systems. The inaccurate correction of MTRC degrades the quality of Bi-ISAR images. However, it is challenging to correct the MTRC where sparse aperture data exists for Bi-ISAR systems. A joint approach of MTRC correction and sparse high-resolution imaging for Bi-ISAR systems is presented in this paper. First, a Bi-ISAR imaging sparse model-related to MTRC is established based on compress sensing (CS). Second, the target image elements and noise are modeled as the complex Laplace prior, and the Gaussian prior, respectively. Finally, the high-resolution, well-focused image is obtained by the full Bayesian inference method, without manual adjustments of unknown parameters. Simulated results verify the effectiveness and robustness of the proposed algorithm.


Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3279 ◽  
Author(s):  
Huan ◽  
Dai ◽  
Luo ◽  
Ai

The interrupted sampling repeater jamming (ISRJ) is considered an efficient deception method of jamming for coherent radar detection. However, current countermeasure methods against ISRJ interference may fail in detecting weak echoes, particularly when the transmitting power of the jammer is relatively high. In this paper, we propose a novel countermeasure scheme against ISRJ based on Bayesian compress sensing (BCS), where stable target signal can be reconstructed over a relatively large range of signal-to-noise ratio (SNR) for both single target and multi-target scenarios. By deriving the ISRJ jamming strategy, only the unjammed discontinuous time segments are extracted to build a sparse target model for the reconstruction algorithm. An efficient alternate iteration is applied to optimize and solve the maximum a posteriori estimate (MAP) of the sparse targets model. Simulation results demonstrate the robustness of the proposed scheme with low SNR or large jammer ratio. Moreover, when compared with traditional FFT or greedy sparsity adaptive matching pursuit algorithm (SAMP), the proposed algorithm significantly improves on the aspects of both the grating lobe level and target detection/false detection probability.


2019 ◽  
Vol 26 (8) ◽  
pp. 5681-5688 ◽  
Author(s):  
Juan Martinez ◽  
Jose Mejia ◽  
Boris Mederos ◽  
Alberto Ochoa ◽  
Oliverio Cruz-Mejía ◽  
...  

2018 ◽  
Vol 176 ◽  
pp. 01018
Author(s):  
Dong Zhang ◽  
Qin Zhang ◽  
Baojun Song ◽  
Guimei Zheng ◽  
Yongshun Zhang

A method of super resolution DOA estimation with incomplete single snapshot data via matrix completion (MC) and compress sensing (CS) is presented. First, the incomplete single snapshot data is reshaped into a low-rank Hankel matrix form and the complete data can be reconstructed through matrix completion. Then, super resolution DOA estimation can be got through CS algorithm using these constructed complete data. Numerical simulations demonstrate that this method can get high accuracy DOA estimation with less number of array elements.


Nukleonika ◽  
2016 ◽  
Vol 61 (1) ◽  
pp. 35-39
Author(s):  
Lech Raczyński ◽  
Paweł Moskal ◽  
Paweł Kowalski ◽  
Wojciech Wiślicki ◽  
Tomasz Bednarski ◽  
...  

Abstract Nowadays, in positron emission tomography (PET) systems, a time of flight (TOF) information is used to improve the image reconstruction process. In TOF-PET, fast detectors are able to measure the difference in the arrival time of the two gamma rays, with the precision enabling to shorten significantly a range along the line-of-response (LOR) where the annihilation occurred. In the new concept, called J-PET scanner, gamma rays are detected in plastic scintillators. In a single strip of J-PET system, time values are obtained by probing signals in the amplitude domain. Owing to compressive sensing (CS) theory, information about the shape and amplitude of the signals is recovered. In this paper, we demonstrate that based on the acquired signals parameters, a better signal normalization may be provided in order to improve the TOF resolution. The procedure was tested using large sample of data registered by a dedicated detection setup enabling sampling of signals with 50-ps intervals. Experimental setup provided irradiation of a chosen position in the plastic scintillator strip with annihilation gamma quanta.


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