Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging
In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recov...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wang, Xueqian [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: IEEE transactions on geoscience and remote sensing - New York, NY : IEEE, 1964, 55(2017), 7, Seite 4072-4081 |
|---|---|
| Übergeordnetes Werk: |
volume:55 ; year:2017 ; number:7 ; pages:4072-4081 |
| Links: |
|---|
| DOI / URN: |
10.1109/TGRS.2017.2687478 |
|---|
| Katalog-ID: |
OLC1994410469 |
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| 520 | |a In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. | ||
| 650 | 4 | |a Radar measurements | |
| 650 | 4 | |a Radar polarimetry | |
| 650 | 4 | |a Matching pursuit algorithms | |
| 650 | 4 | |a Radar imaging | |
| 650 | 4 | |a joint sparsity pattern | |
| 650 | 4 | |a polarimetric radar | |
| 650 | 4 | |a Antenna measurements | |
| 650 | 4 | |a through-wall radar imaging (TWRI) | |
| 650 | 4 | |a Compressive sensing (CS) | |
| 650 | 4 | |a Greedy algorithms | |
| 700 | 1 | |a Li, Gang |4 oth | |
| 700 | 1 | |a Wan, Qun |4 oth | |
| 700 | 1 | |a Burkholder, Robert J |4 oth | |
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10.1109/TGRS.2017.2687478 doi PQ20170721 (DE-627)OLC1994410469 (DE-599)GBVOLC1994410469 (PRQ)i945-74749b626196cf87c5b68d5c92a9baa972467e133e70c34e3b42ff6c4d54706b0 (KEY)0048677920170000055000704072lookaheadhybridmatchingpursuitformultipolarization DE-627 ger DE-627 rakwb eng 620 550 DNB Wang, Xueqian verfasserin aut Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. Radar measurements Radar polarimetry Matching pursuit algorithms Radar imaging joint sparsity pattern polarimetric radar Antenna measurements through-wall radar imaging (TWRI) Compressive sensing (CS) Greedy algorithms Li, Gang oth Wan, Qun oth Burkholder, Robert J oth Enthalten in IEEE transactions on geoscience and remote sensing New York, NY : IEEE, 1964 55(2017), 7, Seite 4072-4081 (DE-627)129601667 (DE-600)241439-9 (DE-576)015095282 0196-2892 nnns volume:55 year:2017 number:7 pages:4072-4081 http://dx.doi.org/10.1109/TGRS.2017.2687478 Volltext http://ieeexplore.ieee.org/document/7914662 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_70 AR 55 2017 7 4072-4081 |
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10.1109/TGRS.2017.2687478 doi PQ20170721 (DE-627)OLC1994410469 (DE-599)GBVOLC1994410469 (PRQ)i945-74749b626196cf87c5b68d5c92a9baa972467e133e70c34e3b42ff6c4d54706b0 (KEY)0048677920170000055000704072lookaheadhybridmatchingpursuitformultipolarization DE-627 ger DE-627 rakwb eng 620 550 DNB Wang, Xueqian verfasserin aut Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. Radar measurements Radar polarimetry Matching pursuit algorithms Radar imaging joint sparsity pattern polarimetric radar Antenna measurements through-wall radar imaging (TWRI) Compressive sensing (CS) Greedy algorithms Li, Gang oth Wan, Qun oth Burkholder, Robert J oth Enthalten in IEEE transactions on geoscience and remote sensing New York, NY : IEEE, 1964 55(2017), 7, Seite 4072-4081 (DE-627)129601667 (DE-600)241439-9 (DE-576)015095282 0196-2892 nnns volume:55 year:2017 number:7 pages:4072-4081 http://dx.doi.org/10.1109/TGRS.2017.2687478 Volltext http://ieeexplore.ieee.org/document/7914662 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_70 AR 55 2017 7 4072-4081 |
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10.1109/TGRS.2017.2687478 doi PQ20170721 (DE-627)OLC1994410469 (DE-599)GBVOLC1994410469 (PRQ)i945-74749b626196cf87c5b68d5c92a9baa972467e133e70c34e3b42ff6c4d54706b0 (KEY)0048677920170000055000704072lookaheadhybridmatchingpursuitformultipolarization DE-627 ger DE-627 rakwb eng 620 550 DNB Wang, Xueqian verfasserin aut Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. Radar measurements Radar polarimetry Matching pursuit algorithms Radar imaging joint sparsity pattern polarimetric radar Antenna measurements through-wall radar imaging (TWRI) Compressive sensing (CS) Greedy algorithms Li, Gang oth Wan, Qun oth Burkholder, Robert J oth Enthalten in IEEE transactions on geoscience and remote sensing New York, NY : IEEE, 1964 55(2017), 7, Seite 4072-4081 (DE-627)129601667 (DE-600)241439-9 (DE-576)015095282 0196-2892 nnns volume:55 year:2017 number:7 pages:4072-4081 http://dx.doi.org/10.1109/TGRS.2017.2687478 Volltext http://ieeexplore.ieee.org/document/7914662 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_70 AR 55 2017 7 4072-4081 |
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10.1109/TGRS.2017.2687478 doi PQ20170721 (DE-627)OLC1994410469 (DE-599)GBVOLC1994410469 (PRQ)i945-74749b626196cf87c5b68d5c92a9baa972467e133e70c34e3b42ff6c4d54706b0 (KEY)0048677920170000055000704072lookaheadhybridmatchingpursuitformultipolarization DE-627 ger DE-627 rakwb eng 620 550 DNB Wang, Xueqian verfasserin aut Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. Radar measurements Radar polarimetry Matching pursuit algorithms Radar imaging joint sparsity pattern polarimetric radar Antenna measurements through-wall radar imaging (TWRI) Compressive sensing (CS) Greedy algorithms Li, Gang oth Wan, Qun oth Burkholder, Robert J oth Enthalten in IEEE transactions on geoscience and remote sensing New York, NY : IEEE, 1964 55(2017), 7, Seite 4072-4081 (DE-627)129601667 (DE-600)241439-9 (DE-576)015095282 0196-2892 nnns volume:55 year:2017 number:7 pages:4072-4081 http://dx.doi.org/10.1109/TGRS.2017.2687478 Volltext http://ieeexplore.ieee.org/document/7914662 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_70 AR 55 2017 7 4072-4081 |
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10.1109/TGRS.2017.2687478 doi PQ20170721 (DE-627)OLC1994410469 (DE-599)GBVOLC1994410469 (PRQ)i945-74749b626196cf87c5b68d5c92a9baa972467e133e70c34e3b42ff6c4d54706b0 (KEY)0048677920170000055000704072lookaheadhybridmatchingpursuitformultipolarization DE-627 ger DE-627 rakwb eng 620 550 DNB Wang, Xueqian verfasserin aut Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. Radar measurements Radar polarimetry Matching pursuit algorithms Radar imaging joint sparsity pattern polarimetric radar Antenna measurements through-wall radar imaging (TWRI) Compressive sensing (CS) Greedy algorithms Li, Gang oth Wan, Qun oth Burkholder, Robert J oth Enthalten in IEEE transactions on geoscience and remote sensing New York, NY : IEEE, 1964 55(2017), 7, Seite 4072-4081 (DE-627)129601667 (DE-600)241439-9 (DE-576)015095282 0196-2892 nnns volume:55 year:2017 number:7 pages:4072-4081 http://dx.doi.org/10.1109/TGRS.2017.2687478 Volltext http://ieeexplore.ieee.org/document/7914662 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO SSG-OPC-GEO GBV_ILN_70 AR 55 2017 7 4072-4081 |
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620 550 DNB Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging Radar measurements Radar polarimetry Matching pursuit algorithms Radar imaging joint sparsity pattern polarimetric radar Antenna measurements through-wall radar imaging (TWRI) Compressive sensing (CS) Greedy algorithms |
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ddc 620 misc Radar measurements misc Radar polarimetry misc Matching pursuit algorithms misc Radar imaging misc joint sparsity pattern misc polarimetric radar misc Antenna measurements misc through-wall radar imaging (TWRI) misc Compressive sensing (CS) misc Greedy algorithms |
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ddc 620 misc Radar measurements misc Radar polarimetry misc Matching pursuit algorithms misc Radar imaging misc joint sparsity pattern misc polarimetric radar misc Antenna measurements misc through-wall radar imaging (TWRI) misc Compressive sensing (CS) misc Greedy algorithms |
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ddc 620 misc Radar measurements misc Radar polarimetry misc Matching pursuit algorithms misc Radar imaging misc joint sparsity pattern misc polarimetric radar misc Antenna measurements misc through-wall radar imaging (TWRI) misc Compressive sensing (CS) misc Greedy algorithms |
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Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging |
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Wang, Xueqian |
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look-ahead hybrid matching pursuit for multipolarization through-wall radar imaging |
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Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging |
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In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. |
| abstractGer |
In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. |
| abstract_unstemmed |
In this paper, we propose a novel greedy algorithm referred to as look-ahead hybrid matching pursuit (LAHMP) for multipolarization through-wall radar imaging (TWRI). From the viewpoint of compressive sensing, the task of multipolarization TWRI can be formulated as a problem of sparsity pattern recovery under the joint sparsity model. A newly developed greedy algorithm for joint sparsity model, hybrid matching pursuit (HMP), combines the strengths of orthogonal matching pursuit and subspace pursuit and improves the accuracy of the sparsity pattern recovery. Besides, the look-ahead strategy can select an optimal atom by evaluating its effectiveness on the overall reconstruction quality. Through integrating the virtues of HMP with the look-ahead strategy, the proposed LAHMP aims to more accurately select atoms corresponding to the true targets behind walls. Experiments based on measured radar data show that, compared to existing greedy algorithms, LAHMP provides better image quality at affordable expense of computational complexity. |
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Look-Ahead Hybrid Matching Pursuit for Multipolarization Through-Wall Radar Imaging |
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