A noise subspace process, based on the eigenvalue decomposition of an array correlation matrix, which uses an implementation of musicalgorithm in two dimensional (2-d) direction of arrival estimation (dOA) problems i...
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ISBN:
(纸本)9781424449682
A noise subspace process, based on the eigenvalue decomposition of an array correlation matrix, which uses an implementation of musicalgorithm in two dimensional (2-d) direction of arrival estimation (dOA) problems is proposed. Simulation results are presented, that illustrate the success of the process to determine the correct azimuth and elevation angles of signal wavefronts impinging on a special L-shape antenna array, consisting of two array branches placed on x and y axes.
The authors investigate the problem of two-dimensional (2d) direction of arrival (dOA) estimation of multiple signals for coprime planar arrays (CPAs) in this study and they propose a computationally efficient 1d part...
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The authors investigate the problem of two-dimensional (2d) direction of arrival (dOA) estimation of multiple signals for coprime planar arrays (CPAs) in this study and they propose a computationally efficient 1d partial spectral search approach based on multiple signal classification (music) algorithm. The conventional 2d music algorithm for CPAs has a great dOA estimation performance, but suffers from a tremendously expensive computational complexity due to the 2d spectral search. To this end, the proposed approach first decreases the dimension of the spectrum function to one dimension and then utilises the linear relationship between the true and ambiguous dOA estimates to form a 1d partial spectral search over a small sector. Finally, the true dOA estimates can be achieved based on the coprime property. The proposed approach can have an impressively gooddOA estimation performance, but with a low computational cost. Simulation results validate the effectiveness and superiority of the proposed approach.
To estimate range and angle information of multiple targets, FMCW MIMO radars have been exploited with 2d music algorithms. To improve estimation accuracy, received signals from multiple FMCW MIMO radars are collected...
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To estimate range and angle information of multiple targets, FMCW MIMO radars have been exploited with 2d music algorithms. To improve estimation accuracy, received signals from multiple FMCW MIMO radars are collected at the data fusion center and processed coherently, which increases data communication overhead and implementation complexity. To resolve them, we propose the distributed2d music algorithm with coordinate transformation, in which 2d music algorithm is operated with respect to the reference radar's coordinate at each radar in a distributed way. Rather than forwarding the raw data of received signal to the fusion center, each radar performs 2dmusic with its own received signal in the transformed coordinates. Accordingly, the distributed radars do not need to report all their measured signals to the data fusion center, but they forward their local cost function values of 2dmusic for the radar image region of interest. The data fusion center can then estimate the range and angle information of targets jointly from the aggregated cost function. By applying the proposed scheme to the experimentally measureddata, its performance is verified in the real environment test.
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