A Novel PARAFAC Model for Processing the Nested Vector-Sensor Array
1
Key Laboratory for Information Science of Electromagnetic Waves (MoE), School of Information Science and Technology, Fudan University, Shanghai 200433, China
2
Nanchang Institute of Technology, Nanchang 330099, China
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(11), 3708; https://doi.org/10.3390/s18113708
Received: 17 August 2018
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Revised: 18 October 2018
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Accepted: 29 October 2018
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Published: 31 October 2018
(This article belongs to the Section Physical Sensors)
In this paper, a novel parallel factor (PARAFAC) model for processing the nested vector-sensor array is proposed. It is first shown that a nested vector-sensor array can be divided into multiple nested scalar-sensor subarrays. By means of the autocorrelation matrices of the measurements of these subarrays and the cross-correlation matrices among them, it is then demonstrated that these subarrays can be transformed into virtual scalar-sensor uniform linear arrays (ULAs). When the measurement matrices of these scalar-sensor ULAs are combined to form a third-order tensor, a novel PARAFAC model is obtained, which corresponds to a longer vector-sensor ULA and includes all of the measurements of the difference co-array constructed from the original nested vector-sensor array. Analyses show that the proposed PARAFAC model can fully use all of the measurements of the difference co-array, instead of its partial measurements as the reported models do in literature. It implies that all of the measurements of the difference co-array can be fully exploited to do the 2-D direction of arrival (DOA) and polarization parameter estimation effectively by a PARAFAC decomposition method so that both the better estimation performance and slightly improved identifiability are achieved. Simulation results confirm the efficiency of the proposed model.
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Keywords:
direction of arrival estimation; nested array; vector sensor; parallel factor (PARAFAC) decomposition
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MDPI and ACS Style
Rao, W.; Li, D.; Zhang, J.Q. A Novel PARAFAC Model for Processing the Nested Vector-Sensor Array. Sensors 2018, 18, 3708. https://doi.org/10.3390/s18113708
AMA Style
Rao W, Li D, Zhang JQ. A Novel PARAFAC Model for Processing the Nested Vector-Sensor Array. Sensors. 2018; 18(11):3708. https://doi.org/10.3390/s18113708
Chicago/Turabian StyleRao, Wei, Dan Li, and Jian Q. Zhang. 2018. "A Novel PARAFAC Model for Processing the Nested Vector-Sensor Array" Sensors 18, no. 11: 3708. https://doi.org/10.3390/s18113708
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