Space-Time Adaptive Processing by Employing Structure-Aware Two-Level Block Sparsity
Traditional radar space-time adaptive processing (STAP) cannot efficiently suppress heterogeneous clutter because of a small number of independent and identically distributed training snapshots. In the article, we propose a new STAP approach exploiting structure-aware two-level block sparsity (STBS)...
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| Published in | IEEE journal of selected topics in applied earth observations and remote sensing Vol. 14; pp. 6386 - 6397 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Piscataway
IEEE
2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1939-1404 2151-1535 2151-1535 |
| DOI | 10.1109/JSTARS.2021.3090069 |
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| Abstract | Traditional radar space-time adaptive processing (STAP) cannot efficiently suppress heterogeneous clutter because of a small number of independent and identically distributed training snapshots. In the article, we propose a new STAP approach exploiting structure-aware two-level block sparsity (STBS) of radar echoes, namely STBS-STAP. It enhances the performance on clutter suppression and target detection with limited training snapshots. The clutter angle-Doppler profile always appears in a continuous diagonal clustering structure and the radar echoes at the adjacent range cells commonly share the same sparse pattern. STBS-STAP employs STBS, i.e., both the diagonal clustering structure and the common sparsity property, to acquire a precise clutter covariance matrix estimation. Thus, the new STBS-STAP achieves better performance on clutter suppression compared with existing STAP methods with a small number of training samples. Besides, STBS-STAP achieves superior target detection performance due to the precise estimation of the statistical properties of the clutter. The superiority of STBS-STAP is verified by experiments on both simulated data and measured Mountain-Top data. |
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| AbstractList | Traditional radar space-time adaptive processing (STAP) cannot efficiently suppress heterogeneous clutter because of a small number of independent and identically distributed training snapshots. In the article, we propose a new STAP approach exploiting structure-aware two-level block sparsity (STBS) of radar echoes, namely STBS-STAP. It enhances the performance on clutter suppression and target detection with limited training snapshots. The clutter angle-Doppler profile always appears in a continuous diagonal clustering structure and the radar echoes at the adjacent range cells commonly share the same sparse pattern. STBS-STAP employs STBS, i.e., both the diagonal clustering structure and the common sparsity property, to acquire a precise clutter covariance matrix estimation. Thus, the new STBS-STAP achieves better performance on clutter suppression compared with existing STAP methods with a small number of training samples. Besides, STBS-STAP achieves superior target detection performance due to the precise estimation of the statistical properties of the clutter. The superiority of STBS-STAP is verified by experiments on both simulated data and measured Mountain-Top data. |
| Author | He, You Jiang, Zhizhuo Li, Gang Wang, Xueqian Zhang, Xiao-Ping |
| Author_xml | – sequence: 1 givenname: Zhizhuo orcidid: 0000-0002-5269-2753 surname: Jiang fullname: Jiang, Zhizhuo email: jzz16@mails.tsinghua.edu.cn organization: Department of Electronic Engineering, Tsinghua University, Beijing, China – sequence: 2 givenname: Xueqian orcidid: 0000-0002-8632-6073 surname: Wang fullname: Wang, Xueqian email: wangxueqian@mail.tsinghua.edu.cn organization: Department of Electronic Engineering, Tsinghua University, Beijing, China – sequence: 3 givenname: Gang orcidid: 0000-0001-9755-2781 surname: Li fullname: Li, Gang email: gangli@tsinghua.edu.cn organization: Department of Electronic Engineering, Tsinghua University, Beijing, China – sequence: 4 givenname: Xiao-Ping orcidid: 0000-0001-5241-0069 surname: Zhang fullname: Zhang, Xiao-Ping email: xzhang@ee.ryerson.ca organization: Department of Electrical, Computer and Biomedical Engineering, Ryerson University, Toronto, ON, Canada – sequence: 5 givenname: You orcidid: 0000-0002-6111-340X surname: He fullname: He, You email: heyou_f@126.com organization: Research Institute of Information Fusion, Naval Aviation University, Yantai, China |
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| References | ref57 ref13 ref56 ref12 ref58 ref14 ref53 ref52 ref55 ref11 ref54 ref10 ref17 ref16 ref19 ref18 ref51 ref50 yang (ref24) 2017; 53 ref46 ref45 sun (ref30) 0 ref48 ref47 ref42 ref41 ref44 ref43 ref49 ref8 ref9 ref4 ref3 ref6 guerci (ref15) 2003 ref5 ref40 ref35 ref34 ref37 wu (ref36) 2015; 22 ref31 ref33 ref32 ref2 ref1 ref39 ref38 ref23 wu (ref65) 2015; 9 ref26 ref25 ref64 ref20 ref63 ward (ref7) 1994 ref22 ref28 ref27 ref29 wang (ref21) 2017; 11 koller (ref59) 2009 ref60 ref62 sundman (ref61) 2014; 105 |
| References_xml | – volume: 22 start-page: 430 year: 2015 ident: ref36 article-title: Multi-task Bayesian compressive sensing exploiting intra-task dependency publication-title: IEEE Signal Process Lett doi: 10.1109/LSP.2014.2360688 – ident: ref16 doi: 10.1109/7.7181 – ident: ref17 doi: 10.1016/0165-1684(96)00007-2 – ident: ref9 doi: 10.1109/TGRS.2016.2561308 – ident: ref47 doi: 10.1109/LSP.2020.3010161 – ident: ref53 doi: 10.1109/JSTARS.2014.2359250 – ident: ref45 doi: 10.1007/s11045-021-00784-x – ident: ref39 doi: 10.21236/ADA520187 – ident: ref54 doi: 10.1016/j.patcog.2017.11.016 – ident: ref37 doi: 10.1109/ICASSP.2019.8682628 – ident: ref41 doi: 10.1109/TAES.2019.2921141 – ident: ref10 doi: 10.1109/JSTARS.2015.2438898 – ident: ref11 doi: 10.1109/TAES.2017.2650639 – ident: ref33 doi: 10.1016/j.dsp.2015.06.011 – year: 2009 ident: ref59 publication-title: Probabilistic Graphical Models-Principles and Techniques – ident: ref44 doi: 10.1016/j.sigpro.2018.05.015 – ident: ref55 doi: 10.1109/TGRS.2013.2292074 – ident: ref57 doi: 10.1109/TIT.2007.909108 – ident: ref46 doi: 10.1109/LGRS.2018.2865536 – ident: ref3 doi: 10.1109/JSTARS.2020.2981046 – volume: 105 start-page: 298 year: 2014 ident: ref61 article-title: Distributed greedy pursuit algorithms publication-title: Signal Process doi: 10.1016/j.sigpro.2014.05.027 – ident: ref32 doi: 10.1109/TSP.2010.2044837 – ident: ref5 doi: 10.1109/RADAR.2019.8835816 – ident: ref49 doi: 10.1049/ip-rsn:20010557 – ident: ref1 doi: 10.1109/JSTARS.2018.2874128 – ident: ref2 doi: 10.1016/j.sigpro.2020.107669 – volume: 53 start-page: 2756 year: 2017 ident: ref24 article-title: Sparsity-based STAP using alternating direction method with gain/phase errors publication-title: IEEE Trans Aerosp Electron Syst doi: 10.1109/TAES.2017.2714938 – ident: ref14 doi: 10.1109/TGRS.2019.2901126 – ident: ref22 doi: 10.1109/TAES.2018.2805141 – ident: ref38 doi: 10.1109/TGRS.2017.2764920 – ident: ref34 doi: 10.1109/RADAR.2015.7131061 – ident: ref4 doi: 10.1109/JSTARS.2019.2956183 – ident: ref42 doi: 10.1117/1.JRS.14.026522 – ident: ref58 doi: 10.1109/MSP.2010.938029 – ident: ref27 doi: 10.1016/j.sigpro.2011.04.006 – ident: ref60 doi: 10.1109/TIT.2013.2273491 – ident: ref20 doi: 10.1109/TSP.2012.2222387 – ident: ref13 doi: 10.1109/TSP.2010.2048212 – ident: ref64 doi: 10.1109/LGRS.2016.2635104 – ident: ref43 doi: 10.1109/TSP.2019.2957640 – year: 0 ident: ref30 article-title: Airborne radar STAP using sparse recovery of clutter spectrum – ident: ref62 doi: 10.1049/PBRA021E – ident: ref25 doi: 10.1016/j.sigpro.2016.06.023 – ident: ref52 doi: 10.1109/LGRS.2012.2236639 – year: 2003 ident: ref15 publication-title: Space-Time Adaptive Processing for Radar – volume: 11 start-page: 177 year: 2017 ident: ref21 article-title: Clutter nulling space-time adaptive processing algorithm based on sparse representation for airborne radar publication-title: IET Radar Sonar Navigat doi: 10.1049/iet-rsn.2016.0118 – ident: ref48 doi: 10.1049/iet-rsn.2017.0425 – ident: ref8 doi: 10.1109/MAES.2004.1263229 – ident: ref19 doi: 10.1109/JSTSP.2015.2464187 – ident: ref18 doi: 10.1109/TCOMM.2002.1010618 – ident: ref28 doi: 10.1109/TSP.2005.849172 – ident: ref51 doi: 10.1109/TGRS.2015.2470518 – ident: ref12 doi: 10.1109/TGRS.2013.2274593 – ident: ref50 doi: 10.1109/TSP.2011.2172435 – ident: ref56 doi: 10.1109/78.157297 – year: 1994 ident: ref7 publication-title: Space-time adaptive processing for airborne radar – ident: ref31 doi: 10.1111/j.1467-9868.2005.00532.x – ident: ref40 doi: 10.1049/iet-rsn.2018.5307 – ident: ref29 doi: 10.1109/IGARSS.2009.5417664 – ident: ref23 doi: 10.1109/TSP.2016.2569471 – ident: ref35 doi: 10.1109/LSP.2013.2292589 – ident: ref63 doi: 10.1109/ICASSP.1996.543572 – ident: ref26 doi: 10.1049/iet-spr.2016.0183 – volume: 9 start-page: 778 year: 2015 ident: ref65 article-title: Robust training samples selection algorithm based on spectral similarity for space-time adaptive processing in heterogeneous interference environments publication-title: IET Radar Sonar Navig doi: 10.1049/iet-rsn.2014.0285 – ident: ref6 doi: 10.1109/TAES.1973.309792 |
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| SubjectTerms | Airborne radar Block sparsity Clustering Clutter Covariance matrix Detection Doppler sonar Echoes Estimation Mountains Object detection Radar Radar clutter radar clutter suppression Radar echoes Space-time adaptive processing space-time adaptive processing (STAP) Spacetime Sparsity Statistical methods structure-aware two-level block sparsity-based STAP (STBS-STAP) Target detection Training |
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| Title | Space-Time Adaptive Processing by Employing Structure-Aware Two-Level Block Sparsity |
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