Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm
Non-Gaussian impulsive noise widely exists in the real world, this paper takes the α-stable distribution as the mathematical model of non-Gaussian impulsive noise and works on the joint direction-of-arrival (DOA) and range estimation problem of near-field signals in impulsive noise environment. Sinc...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-04-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/4/1066 |
| _version_ | 1798000000495517696 |
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| author | Sen Li Bing Li Bin Lin Xiaofang Tang Rongxi He |
| author_facet | Sen Li Bing Li Bin Lin Xiaofang Tang Rongxi He |
| author_sort | Sen Li |
| collection | DOAJ |
| description | Non-Gaussian impulsive noise widely exists in the real world, this paper takes the α-stable distribution as the mathematical model of non-Gaussian impulsive noise and works on the joint direction-of-arrival (DOA) and range estimation problem of near-field signals in impulsive noise environment. Since the conventional algorithms based on the classical second order correlation statistics degenerate severely in the impulsive noise environment, this paper adopts two robust correlations, the fractional lower order correlation (FLOC) and the nonlinear transform correlation (NTC), and presents two related near-field localization algorithms. In our proposed algorithms, by exploring the symmetrical characteristic of the array, we construct the robust far-field approximate correlation vector in relation with the DOA only, which allows for bearing estimation based on the sparse reconstruction. With the estimated bearing, the range can consequently be obtained by the sparse reconstruction of the output of a virtual array. The proposed algorithms have the merits of good noise suppression ability, and their effectiveness is demonstrated by the computer simulation results. |
| first_indexed | 2024-04-11T11:13:18Z |
| format | Article |
| id | doaj.art-d68ffcea50d144d9bcfd1a081e7ade31 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:13:18Z |
| publishDate | 2018-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d68ffcea50d144d9bcfd1a081e7ade312022-12-22T04:27:25ZengMDPI AGSensors1424-82202018-04-01184106610.3390/s18041066s18041066Sparse Reconstruction Based Robust Near-Field Source Localization AlgorithmSen Li0Bing Li1Bin Lin2Xiaofang Tang3Rongxi He4College of Information and Science Technology, Dalian Maritime University, Dalian 116026, ChinaCollege of Information and Science Technology, Dalian Maritime University, Dalian 116026, ChinaCollege of Information and Science Technology, Dalian Maritime University, Dalian 116026, ChinaCollege of Information and Science Technology, Dalian Maritime University, Dalian 116026, ChinaCollege of Information and Science Technology, Dalian Maritime University, Dalian 116026, ChinaNon-Gaussian impulsive noise widely exists in the real world, this paper takes the α-stable distribution as the mathematical model of non-Gaussian impulsive noise and works on the joint direction-of-arrival (DOA) and range estimation problem of near-field signals in impulsive noise environment. Since the conventional algorithms based on the classical second order correlation statistics degenerate severely in the impulsive noise environment, this paper adopts two robust correlations, the fractional lower order correlation (FLOC) and the nonlinear transform correlation (NTC), and presents two related near-field localization algorithms. In our proposed algorithms, by exploring the symmetrical characteristic of the array, we construct the robust far-field approximate correlation vector in relation with the DOA only, which allows for bearing estimation based on the sparse reconstruction. With the estimated bearing, the range can consequently be obtained by the sparse reconstruction of the output of a virtual array. The proposed algorithms have the merits of good noise suppression ability, and their effectiveness is demonstrated by the computer simulation results.http://www.mdpi.com/1424-8220/18/4/1066near-fileddirection of arrivalrange estimationimpulsive noisesparse reconstructionrobust correlation |
| spellingShingle | Sen Li Bing Li Bin Lin Xiaofang Tang Rongxi He Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm Sensors near-filed direction of arrival range estimation impulsive noise sparse reconstruction robust correlation |
| title | Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm |
| title_full | Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm |
| title_fullStr | Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm |
| title_full_unstemmed | Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm |
| title_short | Sparse Reconstruction Based Robust Near-Field Source Localization Algorithm |
| title_sort | sparse reconstruction based robust near field source localization algorithm |
| topic | near-filed direction of arrival range estimation impulsive noise sparse reconstruction robust correlation |
| url | http://www.mdpi.com/1424-8220/18/4/1066 |
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