Results 241 to 250 of about 103,110 (286)
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Stochastic optimization of linear sparse arrays
IEEE Journal of Oceanic Engineering, 1999In conventional beamforming systems, the use of aperiodic arrays is a powerful way to obtain high resolution employing few elements and avoiding the presence of grating lobes. The optimized design of such arrays is a required task in order to control the side-lobe level and distribution.
TRUCCO, ANDREA, V. MURINO
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Tensor MUSIC in multidimensional sparse arrays
2015 49th Asilomar Conference on Signals, Systems and Computers, 2015Tensor-based MUSIC algorithms have been successfully applied to parameter estimation in array processing. In this paper, we apply these for sparse arrays, such as nested arrays and coprime arrays, which are known to boost the degrees of freedom to O(N2) given O(N) sensors.
Chun-Lin Liu, P. P. Vaidyanathan
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Difference bases and sparse sensor arrays
IEEE Transactions on Information Theory, 1993Difference bases are discussed and their relevance to sensor arrays is described. Several new analytical difference base structures that result in near optimal low-redundancy sensor arrays are introduced. Algorithms are also presented for efficiently obtaining sparse sensor arrays and/or difference bases.
Darel A. Linebarger +2 more
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Proceedings of the 34th ACM International Conference on Supercomputing, 2020
While systolic arrays are widely used for dense-matrix operations, they are seldom used for sparse-matrix operations. In this paper, we show how a systolic array of Multiply-and-Accumulate (MAC) units, similar to Google's Tensor Processing Unit (TPU), can be adapted to efficiently handle sparse matrices.
Xin He 0011 +9 more
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While systolic arrays are widely used for dense-matrix operations, they are seldom used for sparse-matrix operations. In this paper, we show how a systolic array of Multiply-and-Accumulate (MAC) units, similar to Google's Tensor Processing Unit (TPU), can be adapted to efficiently handle sparse matrices.
Xin He 0011 +9 more
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A Beamformer Based on Sparse Array with Various Array Structures
2018The degrees of freedom (DOF) of the adaptive beamformer based on conventional linear array is limited by the number of physical array sensors. One way to enhance the DOF is to choose sparse array, whose DOF is greater than the number of sensors in the array.
Yanqi Fan +3 more
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DOA Estimation for Sparse Array via Sparse Signal Reconstruction
IEEE Transactions on Aerospace and Electronic Systems, 2013The problem of direction-of-arrival (DOA) estimation for sparse array is addressed. The perspective that DOA estimation in virtual array response model can be cast as the problem of sparse recovery is introduced. Two methods are proposed, based on different optimization problems, which are solvable using second-order cone (SOC) programming. Without the
Nan Hu 0001 +3 more
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Sparse Bayesian learning for beamforming using sparse linear arrays
The Journal of the Acoustical Society of America, 2018Sparse linear arrays such as co-prime and nested arrays can resolve more sources than the number of sensors. In contrast, uniform linear arrays (ULA) cannot resolve more sources than the number of sensors. This paper demonstrates this using Sparse Bayesian learning (SBL) and co-array MUSIC for single frequency beamforming.
Santosh, Nannuru +4 more
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Low Sidelobe Sparse Array Processing
Digital Signal Processing, 2002Abstract Foster, S., Low Sidelobe Sparse Array Processing, Digital Signal Processing 12 (2002) 360–371 The coherent multiweight beamformer (CMWB) recently proposed by the author is analyzed from the point of view of its co-array structure. It is shown that for certain classes of sparse arrays it is possible to design CMWB beamformers to an ...
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2012 International Conference on Signal Processing and Communications (SPCOM), 2012
Nested and coprime arrays are sparse arrays which can identify O(m2) sources using only m sensors. Systematic algorithms have recently been developed for such identification. These algorithms are traditionally implemented by performing MUSIC or a similar algorithm in the difference-coarray domain.
Vaidyanathan, P. P., Pal, Piya
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Nested and coprime arrays are sparse arrays which can identify O(m2) sources using only m sensors. Systematic algorithms have recently been developed for such identification. These algorithms are traditionally implemented by performing MUSIC or a similar algorithm in the difference-coarray domain.
Vaidyanathan, P. P., Pal, Piya
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Sparse and irregular sampling in array processing
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002Rule-based thinning and element placement methods are first discussed. This includes random arrays, binned random arrays, periodic thinning, element shadowing properties, and fractal arrays. The algorithmic optimization of layouts of 1-D and 2-D sparse arrays is presented and it is empirically derived that the peak sidelobe level for an array with K ...
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