Energy-efficient distributed estimation algorithm for wireless sensor networks based on covariance intersection with eigendecomposition
The paper introduces and assesses the Eigenvalue Covariance Intersection (EVCI) algorithm for data fusion in Wireless Sensor Networks. The EVCI aims to enhance information fusion efficiency, reduce transmitted data, and potentially extend network lifespan. By conducting the eigendecomposition of cov...
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| Veröffentlicht in: | Metrology and Measurement systems 2024-11, Vol.31 (3), p.465-480 |
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| container_title | Metrology and Measurement systems |
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| creator | Pasek, Przemysław Kaniewski, Piotr |
| description | The paper introduces and assesses the Eigenvalue Covariance Intersection (EVCI) algorithm for data fusion in Wireless Sensor Networks. The EVCI aims to enhance information fusion efficiency, reduce transmitted data, and potentially extend network lifespan. By conducting the eigendecomposition of covariance matrices, the EVCI evaluates the utility of eigenvectors and strategically employs only those positively impacting estimate accuracy. Through simulations and comparisons with the Covariance Intersection (CI) algorithm, the study demonstrates EVCI’s ability to maintain accuracy alongside with significant energy savings. The paper provides insights into popular data fusion algorithms, the concept of the EVCI, used formulas, and selected simulation results. |
| doi_str_mv | 10.24425/mms.2024.150290 |
| format | Article |
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| fulltext | fulltext |
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| ispartof | Metrology and Measurement systems, 2024-11, Vol.31 (3), p.465-480 |
| issn | 2300-1941 2080-9050 2300-1941 |
| language | eng |
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| source | DOAJ Directory of Open Access Journals |
| subjects | Accuracy Algorithms Cost control Covariance matrix Data integration Data transmission Eigenvalues Eigenvectors Energy consumption Energy efficiency Multisensor fusion Random variables Sensors Wireless sensor networks |
| title | Energy-efficient distributed estimation algorithm for wireless sensor networks based on covariance intersection with eigendecomposition |
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