Toward Wide-Frequency-Range Direction Finding With Support Vector Regression
| Autor: | Liu-Li Wu, Zhitao Huang, Zhang-meng Liu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Direction finding
Covariance matrix Computer science Computation 020206 networking & telecommunications 02 engineering and technology Toeplitz matrix Computer Science Applications Support vector machine Dimension (vector space) Modeling and Simulation 0202 electrical engineering electronic engineering information engineering Feature (machine learning) Range (statistics) Electrical and Electronic Engineering Algorithm |
| Zdroj: | IEEE Communications Letters. 23:1029-1032 |
| ISSN: | 2373-7891 1089-7798 |
| DOI: | 10.1109/lcomm.2019.2910253 |
| Popis: | This letter presents a support vector regression-based direction finding scheme in a wide range of frequencies. The proposed solution consists of two innovations: preprocessing and post-processing. Preprocessing takes advantage of the conjugate symmetry and Toeplitz property of the array covariance matrix to reduce the dimension of the input feature. Post-processing provides the directions of signals with different frequencies by exploiting the inherent relationship between direction and frequency. The experimental results show that this strategy is able to complete wide-frequency-range direction finding with high estimation accuracy and computation efficiency. |
| Databáze: | OpenAIRE |
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