Fractional difference co-array perspective for wideband signal DOA estimation
In recent years, much attention has been focused on difference co-array perspective in DOA estimation field due to its ability to increase the degrees of freedom and to detect more sources than sensors. In this article, a fractional difference co-array perspective (FrDCA) is proposed by vectorizing...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2018
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| Online Access: | https://hdl.handle.net/10356/88040 http://hdl.handle.net/10220/46892 |
| _version_ | 1811687399073251328 |
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| author | Liu, Jian-Yan Lu, Yi-Long Zhang, Yan-Mei Wang, Wei-Jiang |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Liu, Jian-Yan Lu, Yi-Long Zhang, Yan-Mei Wang, Wei-Jiang |
| author_sort | Liu, Jian-Yan |
| collection | NTU |
| description | In recent years, much attention has been focused on difference co-array perspective in DOA estimation field due to its ability to increase the degrees of freedom and to detect more sources than sensors. In this article, a fractional difference co-array perspective (FrDCA) is proposed by vectorizing structured second-order statistics matrices instead of conventional zero-lag covariance matrix. As a result, not only conventional virtual sensors but also the fractional ones can be utilized to further increase the degrees of freedom. In a sense, the proposed perspective can be viewed as an extended structured model to generate virtual sensors. Then, as a case study, four DOA estimation algorithms for wideband signal based on the FrDCA perspective are specifically presented. The fractional virtual sensors can be generated by dividing the wideband signal into many sub-band signals. Accordingly, the degree of freedom and the maximum number of resolvable sources are increased. The corresponding numerical simulation results validate the advantages and the effectiveness of the proposed perspective. |
| first_indexed | 2024-10-01T05:15:41Z |
| format | Journal Article |
| id | ntu-10356/88040 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:15:41Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/880402020-03-07T13:57:25Z Fractional difference co-array perspective for wideband signal DOA estimation Liu, Jian-Yan Lu, Yi-Long Zhang, Yan-Mei Wang, Wei-Jiang School of Electrical and Electronic Engineering Fractional Difference Co-array Wideband Signal DOA Estimation DRNTU::Engineering::Electrical and electronic engineering In recent years, much attention has been focused on difference co-array perspective in DOA estimation field due to its ability to increase the degrees of freedom and to detect more sources than sensors. In this article, a fractional difference co-array perspective (FrDCA) is proposed by vectorizing structured second-order statistics matrices instead of conventional zero-lag covariance matrix. As a result, not only conventional virtual sensors but also the fractional ones can be utilized to further increase the degrees of freedom. In a sense, the proposed perspective can be viewed as an extended structured model to generate virtual sensors. Then, as a case study, four DOA estimation algorithms for wideband signal based on the FrDCA perspective are specifically presented. The fractional virtual sensors can be generated by dividing the wideband signal into many sub-band signals. Accordingly, the degree of freedom and the maximum number of resolvable sources are increased. The corresponding numerical simulation results validate the advantages and the effectiveness of the proposed perspective. Published version 2018-12-10T03:34:55Z 2019-12-06T16:54:43Z 2018-12-10T03:34:55Z 2019-12-06T16:54:43Z 2016 Journal Article Liu, J.-Y., Lu, Y.-L., Zhang, Y.-M., & Wang, W.-J. (2016). Fractional difference co-array perspective for wideband signal DOA estimation. EURASIP Journal on Advances in Signal Processing, 2016(1), 133-. doi:10.1186/s13634-016-0426-z 1687-6172 https://hdl.handle.net/10356/88040 http://hdl.handle.net/10220/46892 10.1186/s13634-016-0426-z en EURASIP Journal on Advances in Signal Processing © 2016 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 12 p. application/pdf |
| spellingShingle | Fractional Difference Co-array Wideband Signal DOA Estimation DRNTU::Engineering::Electrical and electronic engineering Liu, Jian-Yan Lu, Yi-Long Zhang, Yan-Mei Wang, Wei-Jiang Fractional difference co-array perspective for wideband signal DOA estimation |
| title | Fractional difference co-array perspective for wideband signal DOA estimation |
| title_full | Fractional difference co-array perspective for wideband signal DOA estimation |
| title_fullStr | Fractional difference co-array perspective for wideband signal DOA estimation |
| title_full_unstemmed | Fractional difference co-array perspective for wideband signal DOA estimation |
| title_short | Fractional difference co-array perspective for wideband signal DOA estimation |
| title_sort | fractional difference co array perspective for wideband signal doa estimation |
| topic | Fractional Difference Co-array Wideband Signal DOA Estimation DRNTU::Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/88040 http://hdl.handle.net/10220/46892 |
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