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| Citation: | LIU Zhen, SU Xiaolong, LIU Tianpeng, et al. Matrix differencing method for mixed far-field and near-field source localization[J]. Journal of Radars, 2021, 10(3): 432–442. doi: 10.12000/JR20145
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Matrix Differencing Method for Mixed Far-field andNear-field Source Localization
doi: 10.12000/JR20145
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Abstract
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. -
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References
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- Figure 1. The geometric model of mixed sources
- Figure 2. Flow chart of the mixed source localization based on the covariance differencing method
- Figure 3. Spatial spectrum of mixed sources
- Figure 4. RMSE of mixed sources versus SNR
- Figure 5. RMSE of mixed sources versus snapshots
- Figure 6. Spatial spectrum of near-field source
- Figure 7. Spatial spectrum of far-field source