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PIER PIER B PIER C PIER M PIER Letters
2012-05-29
Constrained Trilinear Decomposition with Application to Array Signal Processing
By
Xu Liu,

    Dr. Xu Liu

    College of Information Science and Technology

    Nanjing University of Aeronautics and Astronautics

    China

    Homepage

Ting Jiang,

    Dr. Ting Jiang

    Nan Jing Panda Technology CO. LTD

    China

    Homepage

Longxiang Yang,

    Dr. Longxiang Yang

    College of Telecommunications and information Engineering

    Nanjing University of Posts &

    China

    Homepage

Hong-Bo Zhu

    Dr. Hong-Bo Zhu

    Nanjing University of Posts and Telecommunications

    China

    Homepage

Progress In Electromagnetics Research, Vol. 128, 195-214, 2012
doi:10.2528/PIER12031410
Abstract
This paper links the constrained trilinear tensor model into array signal processing. The structure properties of baseband signal, such as the Constant-Modulus (CM) and Finite Alphabet (FA) structures which are already known in the receiving array, are exploited in trilinear decomposition. Two novel algorithms for constrained trilinear decomposition are proposed and applied to array signal processing. The distinguishing features of the proposed model and algorithms compared to the traditional trilinear signal processing methods are: (i)~the proposed model has a better performance and lower computation complexity. (ii)~it can still work well even if degeneracy of factors are involved in the data model, which is not valid in traditional algorithms. Simulation results are presented to illustrate the application of the constrained trilinear decomposition to array signal processing and evaluate the performance of the proposed algorithms in DOAs estimation.
Citation
Xu Liu, Ting Jiang, Longxiang Yang, and Hong-Bo Zhu, "Constrained Trilinear Decomposition with Application to Array Signal Processing," Progress In Electromagnetics Research, Vol. 128, 195-214, 2012.
doi:10.2528/PIER12031410
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