Direction-of-Arrival Estimation for Uniform Rectangular Array: A Multilinear Projection Approach. Cao, M., Mao, X., Long, X., & Huang, L. In *2018 26th European Signal Processing Conference (EUSIPCO)*, pages 1237-1241, Sep., 2018.

Paper doi abstract bibtex

Paper doi abstract bibtex

In this paper, elevation and azimuth estimation with uniform rectangular array (URA) is addressed. Since the temporal samples received by the URA could be written into a tensorial form, we introduce the multilinear projection for developing a direction-of-arrival (DOA) estimator. In the noiseless condition, the multilinear projector is orthogonal to the steering matrix of the URA. Thus the proposed DOA estimator is designed to find minimal points of the inner product of the steering vector and the multilinear projector. Based on the multilinear algebraic framework, the proposed approach provides a better subspace estimate than that of the matrix-based subspace. Simulation results are provided to demonstrate the effectiveness of the proposed method.

@InProceedings{8553326, author = {M. Cao and X. Mao and X. Long and L. Huang}, booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)}, title = {Direction-of-Arrival Estimation for Uniform Rectangular Array: A Multilinear Projection Approach}, year = {2018}, pages = {1237-1241}, abstract = {In this paper, elevation and azimuth estimation with uniform rectangular array (URA) is addressed. Since the temporal samples received by the URA could be written into a tensorial form, we introduce the multilinear projection for developing a direction-of-arrival (DOA) estimator. In the noiseless condition, the multilinear projector is orthogonal to the steering matrix of the URA. Thus the proposed DOA estimator is designed to find minimal points of the inner product of the steering vector and the multilinear projector. Based on the multilinear algebraic framework, the proposed approach provides a better subspace estimate than that of the matrix-based subspace. Simulation results are provided to demonstrate the effectiveness of the proposed method.}, keywords = {array signal processing;direction-of-arrival estimation;matrix algebra;vectors;direction-of-arrival estimator;noiseless condition;multilinear projector;steering matrix;URA;DOA estimator;steering vector;multilinear algebraic framework;subspace estimate;matrix-based subspace;direction-of-arrival estimation;uniform rectangular array;multilinear projection approach;azimuth estimation;temporal samples;tensorial form;Direction-of-arrival estimation;Tensile stress;Estimation;Azimuth;Multiple signal classification;Array signal processing;Array signal processing;direction-of-arrival estimation;multilinear algebra;tensor decomposition;uniform rectangular array}, doi = {10.23919/EUSIPCO.2018.8553326}, issn = {2076-1465}, month = {Sep.}, url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570431114.pdf}, }

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