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Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming
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 relativ...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695917/ https://www.ncbi.nlm.nih.gov/pubmed/31349709 http://dx.doi.org/10.3390/s19153279 |
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author | Huan, Sha Dai, Gane Luo, Gaoyong Ai, Shan |
author_facet | Huan, Sha Dai, Gane Luo, Gaoyong Ai, Shan |
author_sort | Huan, Sha |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6695917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66959172019-09-05 Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming Huan, Sha Dai, Gane Luo, Gaoyong Ai, Shan Sensors (Basel) Article 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. MDPI 2019-07-25 /pmc/articles/PMC6695917/ /pubmed/31349709 http://dx.doi.org/10.3390/s19153279 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Huan, Sha Dai, Gane Luo, Gaoyong Ai, Shan Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming |
title | Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming |
title_full | Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming |
title_fullStr | Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming |
title_full_unstemmed | Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming |
title_short | Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming |
title_sort | bayesian compress sensing based countermeasure scheme against the interrupted sampling repeater jamming |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695917/ https://www.ncbi.nlm.nih.gov/pubmed/31349709 http://dx.doi.org/10.3390/s19153279 |
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