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Array Shape Estimation Using Partitioned Eigenstructure Method with Sources in Unknown Localizations

Changgeng Shuai1, 2, Shike Zhang1, 2, Jiaxuan Yang1, 2, Sitong Zhou1, 2
1 Institute of Noise & vibration, Naval University of Engineering, Wuhan, 430033, China
2 National Key Laboratory on Ship Vibration & Noise, Wuhan, 430033, China
The author can be reached at: mjianguo0722@163.com.

Sound & Vibration 2018, 52(4), 2-5. https://doi.org/10.32604/sv.2018.03724

Abstract

Advanced array processing approaches require accurate knowledge of the location of individual element in a sensor array. Most array shape estimation methods require the directions of sources. In this paper, an array shape estimation method based on eigen-decomposition is presented. The directions of sources do not need to be considered in advance and optimal array shape is generated through a series of iterations. To further improve the accuracy of this algorithm, a partitioned eigenstructure method is introduced. Numerical simulations using non-partitioned and partitioned method are conducted to verify the performance of the proposed technique.

Keywords

Array shape estimation, eigenstructure method, partitioned array.

Cite This Article

Shuai, C., Zhang, S., Yang, J., Zhou, S. (2018). Array Shape Estimation Using Partitioned Eigenstructure Method with Sources in Unknown Localizations. Sound & Vibration, 52(4), 2–5.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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