A Sliding Window Data Compression Method for Spatial-Time DOA Estimation
This paper presents a sliding window data compression method for spatial-time direction-of-arrival (DOA) estimation using coprime array. The signal model is firstly formulated by jointly using the temporal and spatial information of the impinging sources. Then, a sliding window data compression proc...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2021/9705617 |
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| author | Pin-Jiao Zhao Guo-Bing Hu Li-Wei Wang |
| author_facet | Pin-Jiao Zhao Guo-Bing Hu Li-Wei Wang |
| author_sort | Pin-Jiao Zhao |
| collection | DOAJ |
| description | This paper presents a sliding window data compression method for spatial-time direction-of-arrival (DOA) estimation using coprime array. The signal model is firstly formulated by jointly using the temporal and spatial information of the impinging sources. Then, a sliding window data compression processing is performed on the array output matrix to realize fast calculation of time average function, and the computational burden has been reduced accordingly. Based on the concept of sum and difference co-array (SDCA), the vectorized conjugate augmented MUSIC is adopted, with which more sources than twice of the physical sensors can be resolved. Additionally, the sparse array robustness to sensor failure has been evaluated by introducing the concept of essential sensors. The theoretical analysis and numerical simulations are provided to confirm the effectiveness performance of the proposed method. |
| format | Article |
| id | doaj-art-64f91c8c873242528ea4e1ad34d9a735 |
| institution | OA Journals |
| issn | 1687-5877 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-64f91c8c873242528ea4e1ad34d9a7352025-08-20T02:06:39ZengWileyInternational Journal of Antennas and Propagation1687-58772021-01-01202110.1155/2021/9705617A Sliding Window Data Compression Method for Spatial-Time DOA EstimationPin-Jiao Zhao0Guo-Bing Hu1Li-Wei Wang2Department of Electronic and Information EngineeringDepartment of Electronic and Information EngineeringNanjing Electronic Devices InstituteThis paper presents a sliding window data compression method for spatial-time direction-of-arrival (DOA) estimation using coprime array. The signal model is firstly formulated by jointly using the temporal and spatial information of the impinging sources. Then, a sliding window data compression processing is performed on the array output matrix to realize fast calculation of time average function, and the computational burden has been reduced accordingly. Based on the concept of sum and difference co-array (SDCA), the vectorized conjugate augmented MUSIC is adopted, with which more sources than twice of the physical sensors can be resolved. Additionally, the sparse array robustness to sensor failure has been evaluated by introducing the concept of essential sensors. The theoretical analysis and numerical simulations are provided to confirm the effectiveness performance of the proposed method.http://dx.doi.org/10.1155/2021/9705617 |
| spellingShingle | Pin-Jiao Zhao Guo-Bing Hu Li-Wei Wang A Sliding Window Data Compression Method for Spatial-Time DOA Estimation International Journal of Antennas and Propagation |
| title | A Sliding Window Data Compression Method for Spatial-Time DOA Estimation |
| title_full | A Sliding Window Data Compression Method for Spatial-Time DOA Estimation |
| title_fullStr | A Sliding Window Data Compression Method for Spatial-Time DOA Estimation |
| title_full_unstemmed | A Sliding Window Data Compression Method for Spatial-Time DOA Estimation |
| title_short | A Sliding Window Data Compression Method for Spatial-Time DOA Estimation |
| title_sort | sliding window data compression method for spatial time doa estimation |
| url | http://dx.doi.org/10.1155/2021/9705617 |
| work_keys_str_mv | AT pinjiaozhao aslidingwindowdatacompressionmethodforspatialtimedoaestimation AT guobinghu aslidingwindowdatacompressionmethodforspatialtimedoaestimation AT liweiwang aslidingwindowdatacompressionmethodforspatialtimedoaestimation AT pinjiaozhao slidingwindowdatacompressionmethodforspatialtimedoaestimation AT guobinghu slidingwindowdatacompressionmethodforspatialtimedoaestimation AT liweiwang slidingwindowdatacompressionmethodforspatialtimedoaestimation |