Abstract
A computationally efficient method for estimating two-dimensional (azimuth and elevation) direction-of-arrival (2-D DOA) of coherently distributed source is presented. Since the coherently distributed source is characterized by four parameters, the azimuth DOA, angular spread of the azimuth DOA, the elevation DOA, and angular spread of the elevation DOA, the computational complexity of the parameter estimation is normally highly demanding. A low-complexity estimation algorithm is proposed based on deduced Schur-Hadamard product steering vector which enables the estimation of 2-D DOA decoupled from that of angular spread of sources. The estimator constructs cross-correlation matrix from subarrays. And then the closed form solution of the elevation and azimuth DOA estimation can be obtained sequentially. Therefore, the proposed method avoids computationally demanding spectral search step and does not involve any eigen decomposition or singular value decomposition as in common subspace techniques such as MUSIC and ESPRIT. Numerical examples illustrate the performance of the method.
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© 2012 Springer-Verlag Berlin Heidelberg
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Han, Y., Wang, J., Zhao, Q., Han, P. (2012). Decoupled 2-D DOA Estimation Algorithm Based on Cross-Correlation Matrix for Coherently Distributed Source. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34487-9_20
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DOI: https://doi.org/10.1007/978-3-642-34487-9_20
Publisher Name: Springer, Berlin, Heidelberg
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