Matches in SemOpenAlex for { <https://semopenalex.org/work/W4205829978> ?p ?o ?g. }
- W4205829978 endingPage "1186" @default.
- W4205829978 startingPage "1172" @default.
- W4205829978 abstract "Massive multiple-input multiple-output (MIMO) radar, enabled by millimeter-wave virtual MIMO techniques, provides great promises to the high-resolution automotive sensing and target detection in unmanned ground/aerial vehicles (UGA/UAV). As a long-established problem, however, existing subspace methods suffer from either high complexity or low accuracy. In this work, we propose two efficient methods, to accomplish fast subspace computation and accurate angle of arrival (AoA) acquisition. By leveraging randomized low-rank approximation, our fast multiple signal classification (MUSIC) methods, relying on random sampling and projection techniques, substantially accelerate the subspace estimation by orders of magnitude. Moreover, we establish the theoretical bounds of our proposed methods, which ensure the accuracy of the approximated pseudo-spectrum. As demonstrated, the pseudo-spectrum acquired by our fast-MUSIC would be highly precise; and the estimated AoA is almost as accurate as standard MUSIC. In contrast, our new methods are tremendously faster than standard MUSIC. Thus, our fast-MUSIC enables the high-resolution real-time environmental sensing with massive MIMO radars, which has great potential in the emerging unmanned systems." @default.
- W4205829978 created "2022-01-25" @default.
- W4205829978 creator A5000159923 @default.
- W4205829978 creator A5019707572 @default.
- W4205829978 creator A5036117084 @default.
- W4205829978 creator A5041756619 @default.
- W4205829978 creator A5063481738 @default.
- W4205829978 date "2022-02-01" @default.
- W4205829978 modified "2023-10-18" @default.
- W4205829978 title "Ultra-Fast Accurate AoA Estimation via Automotive Massive-MIMO Radar" @default.
- W4205829978 cites W1998880686 @default.
- W4205829978 cites W1999580681 @default.
- W4205829978 cites W2008697571 @default.
- W4205829978 cites W2011893133 @default.
- W4205829978 cites W2018744547 @default.
- W4205829978 cites W2019492706 @default.
- W4205829978 cites W2023771239 @default.
- W4205829978 cites W2031006164 @default.
- W4205829978 cites W2050982928 @default.
- W4205829978 cites W2052823331 @default.
- W4205829978 cites W2065205124 @default.
- W4205829978 cites W2073703261 @default.
- W4205829978 cites W2079727548 @default.
- W4205829978 cites W2080115549 @default.
- W4205829978 cites W2081131431 @default.
- W4205829978 cites W2087345669 @default.
- W4205829978 cites W2102098892 @default.
- W4205829978 cites W2113638573 @default.
- W4205829978 cites W2120381494 @default.
- W4205829978 cites W2128131274 @default.
- W4205829978 cites W2130601302 @default.
- W4205829978 cites W2142635246 @default.
- W4205829978 cites W2149755721 @default.
- W4205829978 cites W2153070503 @default.
- W4205829978 cites W2159295545 @default.
- W4205829978 cites W2162654459 @default.
- W4205829978 cites W2167683317 @default.
- W4205829978 cites W2168837636 @default.
- W4205829978 cites W2169749822 @default.
- W4205829978 cites W2244184039 @default.
- W4205829978 cites W2582666574 @default.
- W4205829978 cites W2592680288 @default.
- W4205829978 cites W2611328865 @default.
- W4205829978 cites W2791011781 @default.
- W4205829978 cites W2808060778 @default.
- W4205829978 cites W2933561848 @default.
- W4205829978 cites W2963746586 @default.
- W4205829978 cites W2963784132 @default.
- W4205829978 cites W2965256058 @default.
- W4205829978 cites W2972356219 @default.
- W4205829978 cites W2973146207 @default.
- W4205829978 cites W3017473110 @default.
- W4205829978 cites W3035618061 @default.
- W4205829978 cites W3040360205 @default.
- W4205829978 cites W3068355064 @default.
- W4205829978 cites W3112410551 @default.
- W4205829978 cites W3119155487 @default.
- W4205829978 cites W3138547151 @default.
- W4205829978 cites W3152116210 @default.
- W4205829978 cites W4250888917 @default.
- W4205829978 doi "https://doi.org/10.1109/tvt.2021.3135910" @default.
- W4205829978 hasPublicationYear "2022" @default.
- W4205829978 type Work @default.
- W4205829978 citedByCount "7" @default.
- W4205829978 countsByYear W42058299782022 @default.
- W4205829978 countsByYear W42058299782023 @default.
- W4205829978 crossrefType "journal-article" @default.
- W4205829978 hasAuthorship W4205829978A5000159923 @default.
- W4205829978 hasAuthorship W4205829978A5019707572 @default.
- W4205829978 hasAuthorship W4205829978A5036117084 @default.
- W4205829978 hasAuthorship W4205829978A5041756619 @default.
- W4205829978 hasAuthorship W4205829978A5063481738 @default.
- W4205829978 hasBestOaLocation W42058299782 @default.
- W4205829978 hasConcept C11413529 @default.
- W4205829978 hasConcept C115961682 @default.
- W4205829978 hasConcept C127413603 @default.
- W4205829978 hasConcept C154945302 @default.
- W4205829978 hasConcept C172051844 @default.
- W4205829978 hasConcept C207987634 @default.
- W4205829978 hasConcept C21822782 @default.
- W4205829978 hasConcept C24326235 @default.
- W4205829978 hasConcept C2777121530 @default.
- W4205829978 hasConcept C32834561 @default.
- W4205829978 hasConcept C41008148 @default.
- W4205829978 hasConcept C54197355 @default.
- W4205829978 hasConcept C554190296 @default.
- W4205829978 hasConcept C76155785 @default.
- W4205829978 hasConcept C79403827 @default.
- W4205829978 hasConcept C99498987 @default.
- W4205829978 hasConceptScore W4205829978C11413529 @default.
- W4205829978 hasConceptScore W4205829978C115961682 @default.
- W4205829978 hasConceptScore W4205829978C127413603 @default.
- W4205829978 hasConceptScore W4205829978C154945302 @default.
- W4205829978 hasConceptScore W4205829978C172051844 @default.
- W4205829978 hasConceptScore W4205829978C207987634 @default.
- W4205829978 hasConceptScore W4205829978C21822782 @default.
- W4205829978 hasConceptScore W4205829978C24326235 @default.
- W4205829978 hasConceptScore W4205829978C2777121530 @default.