The existing direction of arrival （DOA） estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction findin...The existing direction of arrival （DOA） estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction finding method using an L-shape electromagnetic vector sensors array is proposed. According to this method, the DOAs of the independent signals and the coherent signals are estimated separately, so that the array aperture can be exploited sufficiently. Firstly, the DOAs of the independent signals are estimated by the estimation of signal parameters via rotational invariance techniques, and the influence of the co- herent signals can be eliminated by utilizing the property of the coherent signals. Then the data covariance matrix containing the information of the coherent signals only is obtained by exploiting the Toeplitz property of the independent signals, and an improved polarimetric angular smoothing technique is proposed to de-correlate the coherent signals. This new method is more practical in actual signal environment than common DOA estimation algorithms and can expand the array aperture. Simulation results are presented to show the estimating performance of the proposed method.展开更多
A novel direction of arrival （DOA） estimation method is proposed when uncorrelated, correlated, and coherent sources coexist under color noise field. The uncorrelated and correlated sources are firstly estimated usi...A novel direction of arrival （DOA） estimation method is proposed when uncorrelated, correlated, and coherent sources coexist under color noise field. The uncorrelated and correlated sources are firstly estimated using the conventional spatial spectrum estimation method, then the noise and uncorrelated sources in Toeplitz structure are eliminated using differencing, finally by exploiting the property of oblique projection, the contributions of correlated sources are then eliminated from the covariance matrix and only the coherent sources remain. So the coherent sources can be estimated by the technique of modified spatial smoothing. The number of sources resolved by this approach can exceed the number of array elements without repeatedly estimating correlated sources. Simulation results demonstrate the effectiveness and efficiency of our proposed method.展开更多
基金supported by the National Natural Science Foundation of China (61102106)the Fundamental Research Funds for the Central Universities (HEUCF1208 HEUCF100801)
文摘The existing direction of arrival （DOA） estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction finding method using an L-shape electromagnetic vector sensors array is proposed. According to this method, the DOAs of the independent signals and the coherent signals are estimated separately, so that the array aperture can be exploited sufficiently. Firstly, the DOAs of the independent signals are estimated by the estimation of signal parameters via rotational invariance techniques, and the influence of the co- herent signals can be eliminated by utilizing the property of the coherent signals. Then the data covariance matrix containing the information of the coherent signals only is obtained by exploiting the Toeplitz property of the independent signals, and an improved polarimetric angular smoothing technique is proposed to de-correlate the coherent signals. This new method is more practical in actual signal environment than common DOA estimation algorithms and can expand the array aperture. Simulation results are presented to show the estimating performance of the proposed method.
基金supported by the National Natural Science Foundation of China(60601016).
文摘A novel direction of arrival （DOA） estimation method is proposed when uncorrelated, correlated, and coherent sources coexist under color noise field. The uncorrelated and correlated sources are firstly estimated using the conventional spatial spectrum estimation method, then the noise and uncorrelated sources in Toeplitz structure are eliminated using differencing, finally by exploiting the property of oblique projection, the contributions of correlated sources are then eliminated from the covariance matrix and only the coherent sources remain. So the coherent sources can be estimated by the technique of modified spatial smoothing. The number of sources resolved by this approach can exceed the number of array elements without repeatedly estimating correlated sources. Simulation results demonstrate the effectiveness and efficiency of our proposed method.
