| Autor: |
Zhen LIU, Xiaolong SU, Tianpeng LIU, Bo PENG, Xin CHEN, Yongxiang LIU |
| Jazyk: |
English<br />Chinese |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Leida xuebao, Vol 10, Iss 3, Pp 432-442 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2095-283X |
| DOI: |
10.12000/JR20145 |
| Popis: |
Mixed source localization plays an important role in passive radars. Aiming at the problem of low accuracy via phase difference method under a uniform circular array, this paper proposes a matrix differencing method for mixed far-field and near-field source localization. First, a two-dimensional MUltiple SIgnal Classification (MUSIC) method was utilized to estimate the azimuth and elevation angles of far-field sources. Thereafter, the covariance matrix difference method was exploited to extract the difference matrix of near-field sources. The azimuth and elevation angles of the far-field sources were estimated using the Estimation of Signal Parameters via Rotational Invariance Techniques-like (ESPRIT-like) method. Furthermore, the distance of the near-field sources was obtained by the one-dimensional MUSIC method. Finally, simulations were performed to verify the performance of the proposed algorithm. The proposed algorithm could effectively identify the mixed source when the two-dimensional Direction-Of-Arrival (DOA) of the far-field and near-field sources were the same. Moreover, the proposed algorithm could improve the accuracy of the mixed source parameter estimation. Results show that when the signal-to-noise ratio was set to 20 dB, the 2-D DOA estimation error of the near-field source was approximately 0.01°, and the distance error of the near-field source was approximately 0.1 m. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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