Majorization-Minimization Based Hybrid Localization Method for High Precision Localization in Wireless Sensor Networks
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| Argitaratua izan da: | Wireless Personal Communications vol. 145, no. 1-2 (Nov 2025), p. 1 |
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| Egile nagusia: | |
| Beste egile batzuk: | , |
| Argitaratua: |
Springer Nature B.V.
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| Gaiak: | |
| Sarrera elektronikoa: | Citation/Abstract Full Text Full Text - PDF |
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| 001 | 3278316665 | ||
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| 022 | |a 0929-6212 | ||
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| 024 | 7 | |a 10.1007/s11277-025-11839-8 |2 doi | |
| 035 | |a 3278316665 | ||
| 045 | 2 | |b d20250101 |b d20250331 | |
| 100 | 1 | |a Panwar, Kuntal |u Indian Institute of Technology, Delhi, Centre for Applied Research in Electronics, New Delhi, India (GRID:grid.503024.0) (ISNI:0000 0004 6828 3019) | |
| 245 | 1 | |a Majorization-Minimization Based Hybrid Localization Method for High Precision Localization in Wireless Sensor Networks | |
| 260 | |b Springer Nature B.V. |c Nov 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper investigates the hybrid source localization problem using the four radio measurements - time of arrival (TOA), time difference of arrival (TDOA), received signal strength (RSS), and angle of arrival (AOA). First, after invoking tractable approximations in the RSS and AOA models, the maximum likelihood estimation (MLE) problem for the hybrid TOA-TDOA-RSS-AOA data model is derived. Then a weighted least-squares problem is formulated from the MLE, which is solved using the principle of the majorization-minimization (MM), resulting in an iterative algorithm with guaranteed convergence. The key feature of the proposed method is that it provides a unified framework where localization using any possible merger out of these four measurements can be implemented as per the requirement/application. Extensive numerical simulations are conducted to study the performance of the proposed method. The obtained results indicate that the hybrid localization model improves the localization accuracy compared to the heterogeneous measurements under different network scenarios, which also includes the presence of non-line of sight (NLOS) errors. | |
| 653 | |a Localization method | ||
| 653 | |a Iterative algorithms | ||
| 653 | |a Accuracy | ||
| 653 | |a Communication | ||
| 653 | |a Angle of arrival | ||
| 653 | |a Sensors | ||
| 653 | |a Wireless sensor networks | ||
| 653 | |a Optimization | ||
| 653 | |a Least squares method | ||
| 653 | |a Signal strength | ||
| 653 | |a Maximum likelihood estimation | ||
| 653 | |a Methods | ||
| 653 | |a Algorithms | ||
| 653 | |a Localization | ||
| 700 | 1 | |a Babu, Prabhu |u Indian Institute of Technology, Delhi, Centre for Applied Research in Electronics, New Delhi, India (GRID:grid.503024.0) (ISNI:0000 0004 6828 3019) | |
| 700 | 1 | |a Jyothi, R. |u University of Iowa, Department of Electrical and Computer Engineering, Iowa City, USA (GRID:grid.214572.7) (ISNI:0000 0004 1936 8294) | |
| 773 | 0 | |t Wireless Personal Communications |g vol. 145, no. 1-2 (Nov 2025), p. 1 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3278316665/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3278316665/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3278316665/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |