Results 231 to 240 of about 402,558 (283)
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On Spatial Power Spectrum and Signal Estimation Using the Pisarenko Framework
IEEE Transactions on Signal Processing, 2008This paper makes use of the Pisarenko framework, originally devised for temporal power spectrum estimation, to introduce a method for spatial power estimation that outperforms the beamforming method (except in extreme cases with serious calibration errors) as well as the Capon method (except in idealized situations with plentiful data and no ...
Petre Stoica, Jian Li, Xing Tan
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Spatial spectrum estimation based on compressive sensing
IET International Radar Conference 2015, 2015The most prominent subspace decomposition methods for spatial spectrum estimation include multiple signal classification algorithm (MUSIC) as well as estimation signal parameter via rotational invariance technique (ESPRIT). However, the drawbacks of MUSIC is that estimating the number of source signals are constraint by the following two aspects: array
Li Wei Li Wei +2 more
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Beamspace Synthetic Spatial Spectrum DOA Estimator
2008 Fourth International Conference on Natural Computation, 2008In this paper, we develop a new estimator of DOA named Synthetic Spatial spectrum Method (SSM) to beamspace processing. Beamspace transformation maps the full dimension sensor space data onto a lower dimension space. Then the SSM deals with covariance matrix of beamspace data directly.
Wang Qiong, You Hong
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Research and simulation of spatial spectrum estimation algorithm
2010 International Conference on Image Analysis and Signal Processing, 2010The spatial spectrum indicates the signal's energy distribution in all directions. If we can get the signal's spatial spectrum, then the signal's direction of arrival (DOA) is known. The paper makes researches on the spatial spectrum estimation algorithms for uniform linear array, and establishes three mathematical models of MUSIC, ESPRIT and Capon ...
null Yang Zhifei +2 more
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Performance analysis of the MVDR spatial spectrum estimator
IEEE Transactions on Signal Processing, 1995The performance of the minimum variance distortionless response spectrum estimator is analyzed. Finite data effects and the sensitivity of the method to random perturbations in the signal model and in the noise covariance matrix are studied. The snapshots are assumed to be complex independent identically distributed Gaussian vectors.
C. Vaidyanathan, K.M. Buckley
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DOA estimation based on a modified spatial spectrum
IET International Radar Conference 2015, 2015A novel direction of arrivals (DOAs) estimation method based on a modified spatial spectrum is proposed in this paper, which can be used for the source number and DOAs estimation of the weak signals in the presence of the strong interferences. First, the eigenvectors of the spatial covariance matrix is sorted according to the descending order of the ...
Fei Huang Fei Huang +2 more
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Time-varying spatial spectrum estimation with a maneuverable towed array
The Journal of the Acoustical Society of America, 2010This paper addresses the problem of field directionality mapping (FDM) or spatial spectrum estimation in dynamic environments with a maneuverable towed acoustic array. Array processing algorithms for towed arrays are typically designed assuming the array is straight, and are thus degraded during tow-ship maneuvers.
Jeffrey S, Rogers, Jeffrey L, Krolik
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Sparse Spatial Spectrum Estimation for Underwater Multi-rank Signals
OCEANS 2018 MTS/IEEE Charleston, 2018Assume a narrowband signal propagate through the ocean waveguide. Due to the waveguide fluctuation, rough boundary effect or random scattering, etc., the signal wavefront would vary from snapshot to snapshot with the signal energy disperse within a small angular bandwidth, resulting in a multi-rank signal covariance.
Guangyu Jiang +3 more
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Platform of Spatial Spectrum Estimation Based on Matlab GUI
Applied Mechanics and Materials, 2014A platform of spatial estimation, which is based on Matlab GUI, was established. We use Matlab to do analysis of different parameters (Signal-to-noise ratio, the number of snapshots, the number of antenna elements, the number of targets) and simulate the results with different algorithm.
Shen Zhao, Xiao Fei Zhang
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Multiple window based minimum variance broadband spatial spectrum estimation
International Conference on Acoustics, Speech, and Signal Processing, 1990The problem of estimating the power received at an array of sensors as a function of direction for broadband environments is addressed. A multiple-window-based processing scheme is proposed to reduce the variance of the power estimates. The windows are data dependent, and are derived from a linearly constrained minimum variance (LCMV) criterion ...
T.-C. Liu, B.D. VanVeen
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