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| To address the problems of high computational complexity and angle mismatch in 2-D DOA estimation using CS theory in the intelligent vehicle radar communication integrated system, this paper proposes a new method based on compressed sensing. Combined with the particularity of L-shaped array structure, this method firstly uses SVD processing to obtain a low-dimensional data matrix; secondly, defines the spatial synthesis angle for secondary dimensionality reduction; then uses the OMP algorithm and mathematical geometry to inversely obtain sparse parameters; finally, the subspace projection is used to achieve angle matching, so as to obtain the correct 2-D DOA estimation result. The theoretical derivation and experimental simulations show that this algorithm greatly reduces the computational complexity and improves the probability of pairing success. It also has obvious advantages for different SNR, array element number and snapshot number. |
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| Keywords:wireless communication technology; radar communication Intergration; compressed sensing(CS); singular value decomposition(SVD); redundant dictionary; subspace projection |
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