Mixed near-field and far-field source localization revised: propagation loss included
| Autor: | Pourya Behmandpoor, Farzan Haddadi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Applied Mathematics 020206 networking & telecommunications Near and far field 02 engineering and technology Bearing (navigation) Signal Computer Science Applications Power (physics) Artificial Intelligence Hardware and Architecture Signal Processing Source localization 0202 electrical engineering electronic engineering information engineering Range (statistics) Path loss 020201 artificial intelligence & image processing Stage (hydrology) Algorithm Software Information Systems |
| Zdroj: | Multidimensional Systems and Signal Processing. 31:711-723 |
| ISSN: | 1573-0824 0923-6082 |
| Popis: | This paper is concerned with source localization when path loss is taken into account. We modify multiple signal classification method to localize near-field sources whose received power is different in the sensors of the array due to path loss. Traditional methods fail to localize the sources, and they also fail to separate the bearing estimation and the range estimation of the sources, when path loss is considered. We suggest a T-shaped array avoiding multidimensional search to estimate source location parameters, separately. At the first step, the ranges of the signal sources are estimated, and then at the second step, the directions of arrival of the sources are estimated using the respective ranges determined at the first stage. The performance of the proposed method is assessed when mixed near-field and far-field sources coexist. Simulation results are presented to show the superior performance of the proposed algorithm compared to the existing techniques and the Cramer–Rao bound. |
| Databáze: | OpenAIRE |
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