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Compressive sensing-based robust off-the-grid stretch processing
Classical stretch processing (SP) obtains high range resolution by compressing large bandwidth signals with narrowband receivers using lower rate analogue-to-digital converters. SP achieves the resolution of the large bandwidth signal by focusing into a limited range window, and by deramping in the...
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Published in: | IET radar, sonar & navigation sonar & navigation, 2017-11, Vol.11 (11), p.1730-1735 |
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container_title | IET radar, sonar & navigation |
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creator | Ilhan, Ihsan Gurbuz, Ali Cafer Arikan, Orhan |
description | Classical stretch processing (SP) obtains high range resolution by compressing large bandwidth signals with narrowband receivers using lower rate analogue-to-digital converters. SP achieves the resolution of the large bandwidth signal by focusing into a limited range window, and by deramping in the analogue domain. SP offers moderate data rate for signal processing for high bandwidth waveforms. Furthermore, if the scene in the examined window is sparse, compressive sensing (CS)-based techniques have the potential to further decrease the required number of measurements. However, CS-based reconstructions are highly affected by model mismatches such as targets that are off-the-grid. This study proposes a sparsity-based iterative parameter perturbation technique for SP that is robust to targets off-the-grid in range or Doppler. The error between reconstructed and actual scenes is measured using Earth mover's distance metric. Performance analyses of the proposed technique are compared with classical CS and SP techniques in terms of data rate, resolution and signal-to-noise ratio. It is shown through simulations that the proposed technique offers robust and high-resolution reconstructions for the same data rate compared with both classical SP- and CS-based techniques. |
doi_str_mv | 10.1049/iet-rsn.2017.0133 |
format | article |
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SP achieves the resolution of the large bandwidth signal by focusing into a limited range window, and by deramping in the analogue domain. SP offers moderate data rate for signal processing for high bandwidth waveforms. Furthermore, if the scene in the examined window is sparse, compressive sensing (CS)-based techniques have the potential to further decrease the required number of measurements. However, CS-based reconstructions are highly affected by model mismatches such as targets that are off-the-grid. This study proposes a sparsity-based iterative parameter perturbation technique for SP that is robust to targets off-the-grid in range or Doppler. The error between reconstructed and actual scenes is measured using Earth mover's distance metric. Performance analyses of the proposed technique are compared with classical CS and SP techniques in terms of data rate, resolution and signal-to-noise ratio. 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SP achieves the resolution of the large bandwidth signal by focusing into a limited range window, and by deramping in the analogue domain. SP offers moderate data rate for signal processing for high bandwidth waveforms. Furthermore, if the scene in the examined window is sparse, compressive sensing (CS)-based techniques have the potential to further decrease the required number of measurements. However, CS-based reconstructions are highly affected by model mismatches such as targets that are off-the-grid. This study proposes a sparsity-based iterative parameter perturbation technique for SP that is robust to targets off-the-grid in range or Doppler. The error between reconstructed and actual scenes is measured using Earth mover's distance metric. Performance analyses of the proposed technique are compared with classical CS and SP techniques in terms of data rate, resolution and signal-to-noise ratio. It is shown through simulations that the proposed technique offers robust and high-resolution reconstructions for the same data rate compared with both classical SP- and CS-based techniques.</description><subject>analogue domain</subject><subject>analogue‐digital conversion</subject><subject>analogue‐to‐digital converters</subject><subject>bandwidth signals</subject><subject>classical stretch processing</subject><subject>compressed sensing</subject><subject>compressive sensing</subject><subject>CS‐based reconstructions</subject><subject>CS‐based techniques</subject><subject>data rate</subject><subject>deramping</subject><subject>Earth mover's distance metric</subject><subject>high bandwidth waveforms</subject><subject>high range resolution</subject><subject>high‐resolution reconstructions</subject><subject>iterative methods</subject><subject>model mismatches</subject><subject>narrowband receivers</subject><subject>perturbation techniques</subject><subject>Research Article</subject><subject>robust off‐the‐grid stretch processing</subject><subject>signal processing</subject><subject>signal reconstruction</subject><subject>signal resolution</subject><subject>signal‐to‐noise ratio</subject><subject>sparsity‐based iterative parameter perturbation technique</subject><subject>waveform analysis</subject><issn>1751-8784</issn><issn>1751-8792</issn><issn>1751-8792</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFkMtOwzAQRS0EEqXwAezyAy7jxI5tVkBFAakCicfacpxxmqpNKjsF9e9JFMQSVjOLOXN1DyGXDGYMuL6qsaMhNrMUmJwBy7IjMmFSMKqkTo9_d8VPyVmMawAhcq4n5GbebncBY6w_MYnYxLqpaGEjlkloi33sktZ72q2QVqEuk9gF7Nwq2YXWDVBTnZMTbzcRL37mlHws7t_nj3T58vA0v11Sl0kpqHQ5MJ9KW2osvdDOWy28Bl5KwZnwVnAsUKG1uQK0zKacOwmpKjHzXuXZlLDxrwttjAG92YV6a8PBMDCDAtMrML0CMygwg4KeuR6Zr3qDh_8B8_r2nN4tABSIHqYjPJyt231o-np_hH0DqL9zUQ</recordid><startdate>201711</startdate><enddate>201711</enddate><creator>Ilhan, Ihsan</creator><creator>Gurbuz, Ali Cafer</creator><creator>Arikan, Orhan</creator><general>The Institution of Engineering and Technology</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>201711</creationdate><title>Compressive sensing-based robust off-the-grid stretch processing</title><author>Ilhan, Ihsan ; Gurbuz, Ali Cafer ; Arikan, Orhan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3775-7c601f27ad9edf59cfa95f904d75415fa54ebe8eaa680ea1a244c7028de3ff863</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>analogue domain</topic><topic>analogue‐digital conversion</topic><topic>analogue‐to‐digital converters</topic><topic>bandwidth signals</topic><topic>classical stretch processing</topic><topic>compressed sensing</topic><topic>compressive sensing</topic><topic>CS‐based reconstructions</topic><topic>CS‐based techniques</topic><topic>data rate</topic><topic>deramping</topic><topic>Earth mover's distance metric</topic><topic>high bandwidth waveforms</topic><topic>high range resolution</topic><topic>high‐resolution reconstructions</topic><topic>iterative methods</topic><topic>model mismatches</topic><topic>narrowband receivers</topic><topic>perturbation techniques</topic><topic>Research Article</topic><topic>robust off‐the‐grid stretch processing</topic><topic>signal processing</topic><topic>signal reconstruction</topic><topic>signal resolution</topic><topic>signal‐to‐noise ratio</topic><topic>sparsity‐based iterative parameter perturbation technique</topic><topic>waveform analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ilhan, Ihsan</creatorcontrib><creatorcontrib>Gurbuz, Ali Cafer</creatorcontrib><creatorcontrib>Arikan, Orhan</creatorcontrib><collection>CrossRef</collection><jtitle>IET radar, sonar & navigation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ilhan, Ihsan</au><au>Gurbuz, Ali Cafer</au><au>Arikan, Orhan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Compressive sensing-based robust off-the-grid stretch processing</atitle><jtitle>IET radar, sonar & navigation</jtitle><date>2017-11</date><risdate>2017</risdate><volume>11</volume><issue>11</issue><spage>1730</spage><epage>1735</epage><pages>1730-1735</pages><issn>1751-8784</issn><issn>1751-8792</issn><eissn>1751-8792</eissn><abstract>Classical stretch processing (SP) obtains high range resolution by compressing large bandwidth signals with narrowband receivers using lower rate analogue-to-digital converters. SP achieves the resolution of the large bandwidth signal by focusing into a limited range window, and by deramping in the analogue domain. SP offers moderate data rate for signal processing for high bandwidth waveforms. Furthermore, if the scene in the examined window is sparse, compressive sensing (CS)-based techniques have the potential to further decrease the required number of measurements. However, CS-based reconstructions are highly affected by model mismatches such as targets that are off-the-grid. This study proposes a sparsity-based iterative parameter perturbation technique for SP that is robust to targets off-the-grid in range or Doppler. The error between reconstructed and actual scenes is measured using Earth mover's distance metric. Performance analyses of the proposed technique are compared with classical CS and SP techniques in terms of data rate, resolution and signal-to-noise ratio. It is shown through simulations that the proposed technique offers robust and high-resolution reconstructions for the same data rate compared with both classical SP- and CS-based techniques.</abstract><pub>The Institution of Engineering and Technology</pub><doi>10.1049/iet-rsn.2017.0133</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | analogue domain analogue‐digital conversion analogue‐to‐digital converters bandwidth signals classical stretch processing compressed sensing compressive sensing CS‐based reconstructions CS‐based techniques data rate deramping Earth mover's distance metric high bandwidth waveforms high range resolution high‐resolution reconstructions iterative methods model mismatches narrowband receivers perturbation techniques Research Article robust off‐the‐grid stretch processing signal processing signal reconstruction signal resolution signal‐to‐noise ratio sparsity‐based iterative parameter perturbation technique waveform analysis |
title | Compressive sensing-based robust off-the-grid stretch processing |
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