The existing SRV-MVDR (semi-real-valued MVDR) algorithm is only applicable to the pressure sensors array and cannot distinguish between mirror radiation sources and real source (DOA fuzzy), and this paper presents a method of vector sensors array SRV-MVDR based on subspace projection. Compared with the existing SRV-MVDR, only half spectrum search is needed to solve the DOA fuzzy problem. No subsequent discrimination is needed. The data collected by vector sensors array are processed jointly by using the idea of dimensionality reduction so that it satisfies the processing condition of SRV-MVDR method. Theoretical analysis and computer simulation show that this method has robustness. At the same time, it is more suitable for low SNR and small snapshots and has broad prospects in practical engineering.
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This work was supported by National Natural Science Foundation (11574120, U1636117); the Natural Science Foundation of Jiangsu Province of China (BK20161359); Postgraduate Research & Practice Innovation Program of Jiangsu Province (SJCX17_0604); The Open Project Program of the Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, China (UASP1503); The Science and Technology on Underwater Acoustic Antagonizing Laboratory, Systems Engineering Research Institute of CSSC(Grant No. MB80038) and Six Talent Peaks project of Jiangsu Province.
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Wang, B., Chen, F. & Ge, H. Subspace projection semi-real-valued MVDR algorithm based on vector sensors array processing. Neural Comput & Applic 32, 173–181 (2020). https://doi.org/10.1007/s00521-018-3791-8
- Vector sensors array
- Half spectrum search