Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  address the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. By exploiting the temporal structure and the multidimensional inherent structure, a fourth-order cross-covariance tensor is formulated to eliminate the effect of spatial colored noise. The higher-order singular value decomposition is utilized for accurate signal subspace estimation. Thereafter, angles are obtained with the shift-invariance technique. The proposed method can achieve automatic pairing of the estimated angles without any virtual aperture loss, thus it has better estimation performance than existing methods. Extensive numerical experiments verify the effectiveness and improvement of our algorithm.
['Fangqing Wen', 'Xiaodong Xiong', 'Jian Su', 'Zijing Zhang']
I am writing a research paper on a idea Angle estimation for bistatic MIMO radar in the presence of spatial colored noise
[{"from": "human", "value": "I am writing a research paper on a idea Angle estimation for bistatic MIMO radar in the presence of spatial colored noise"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  address the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. By exploiting the temporal structure and the multidimensional inherent structure, a fourth-order cross-covariance tensor is formulated to eliminate the effect of spatial colored noise. The higher-order singular value decomposition is utilized for accurate signal subspace estimation. Thereafter, angles are obtained with the shift-invariance technique. The proposed method can achieve automatic pairing of the estimated angles without any virtual aperture loss, thus it has better estimation performance than existing methods. Extensive numerical experiments verify the effectiveness and improvement of our algorithm."}]