摘要
A bi-capon beamforming （BCB） algorithm for multi-input multi-output （MIMO） radar is developed on the basis of correlation domain. By vectorizing the echo matrix and its transpose, the conventional capon cost function is transformed into bi-capon quadratic functions. By calculating two lower dimensional weight vectors with sub-matrices of the correlation matrix, BCB can significantly decrease the computational complexity and the requirement of training samples. In the presence of short data records, BCB can achieve better interference suppression performance than fully adaptive capon algorithm. Simulation results are presented to demonstrate the effectiveness of the proposed method.
A bi-capon beamforming （BCB） algorithm for multi-input multi-output （MIMO） radar is developed on the basis of correlation domain. By vectorizing the echo matrix and its transpose, the conventional capon cost function is transformed into bi-capon quadratic functions. By calculating two lower dimensional weight vectors with sub-matrices of the correlation matrix, BCB can significantly decrease the computational complexity and the requirement of training samples. In the presence of short data records, BCB can achieve better interference suppression performance than fully adaptive capon algorithm. Simulation results are presented to demonstrate the effectiveness of the proposed method.
基金
supported by the National Natural Science Foundation of China (60971111)
the Natural Science Foundation of Shaanxi Province (2011JQ8041)
