Direction of arrival estimation for conformal arrays with diverse polarizations

Zi-yang, Gao; Yong, Xiao

doi:10.1109/icemi.2015.7494229

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…Firstly, the proposed method imposes stronger constraints between the components of the signals. Secondly, the conformal array in [20] essentially belongs to the scalar array from the standpoint of elements while the conformal vectorsensor array presented in this paper belongs to the vector array. And the vector array contains more signal information compared with the scalar array.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…To better demonstrate the performance of the proposed method, Qi's method [3] and Gao's algorithm [20] are included for comparison. We study the performance with a varying SNR from 0 to 30 dB.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Due to the limited length, the relationship between the two fields will be derived in Appendix 2. In addition, from (18,19,20, and 21), we see that the orthogonality of the signal components is reserved. Compared with the conventional methods, such as the long vector algorithm [8], this orthogonality constraint implies stronger relationships between the signal components.…”

Section: Manifold Modeling Of Vector Sensors In the Conformal Arraymentioning

confidence: 99%

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DOA estimation for conformal vector-sensor array using geometric algebra

Tao

Yuan

2017

EURASIP J. Adv. Signal Process.

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In this paper, the problem of direction of arrival (DOA) estimation is considered in the case of multiple polarized signals impinging on the conformal electromagnetic vector-sensor array (CVA). We focus on modeling the manifold holistically by a new mathematical tool called geometric algebra. Compared with existing methods, the presented one has two main advantages. Firstly, it acquires higher resolution by preserving the orthogonality of the signal components. Secondly, it avoids the cumbersome matrix operations while performing the coordinate transformations, and therefore, has a much lower computational complexity. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%