Results 251 to 260 of about 103,159 (268)

Sparsely Populated Antenna Arrays

2013
The chapter begins with a brief introduction to sparse linear arrays. We use interval partitions to define minimum redundancy partitions and almost minimum redundancy partitions that achieve low sidelobe excitation patterns. These arrays assure that the spatial Nyquist condition is satisfied and also attempt to maximize the number of partition ...
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Sparse Sampling in Array Processing

2001
Sparsely sampled irregular arrays and random arrays have been used or proposed in several fields such as radar, sonar, ultrasound imaging, and seismics. We start with an introduction to array processing and then consider the combinatorial problem of finding the best layout of elements in sparse 1-D and 2-D arrays.
S. Holm, A. Austeng, K. Iranpour, J.-F. Hopperstad   +3 more
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Low Sidelobe Sparse Array Processing

Digital Signal Processing, 2002
Abstract 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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DOA Estimation for Sparse Array via Sparse Signal Reconstruction

IEEE Transactions on Aerospace and Electronic Systems, 2013
The 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, Zhongfu Ye, Xu Xu, Ming Bao
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2D Beamforming on Sparse Arrays with Sparse Bayesian Learning

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
Sparse arrays such as co-prime and nested arrays can identify more sources than the number of sensors. This is because their difference co-arrays contain a uniformly spaced virtual array with more elements than the number of sensors in the array. In this paper we demonstrate this using two dimensional co-prime and nested sparse arrays combined with ...
Santosh Nannuru, Peter Gerstoft
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Beamforming of Sparse Cylindrical Arrays

2017
As sparse arrays cost fewer elements, they are less expensive than dense arrays and could be applied widely in antenna and sonar deployment, two sparse cylindrical arrays are proposed in this paper. According to the characteristic of cylindrical array, it can be seen as a linear array whose elements are the identical circular arrays.
Na Wu, Qilian Liang
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Accessing Sparse Arrays in Parallel Memories

1983
The concept of dense and sparse execution of arrays is introduced. Arrays, themselves, can be stored in a dense or sparse manner in a parallel memory with m memory modules. Hardware is proposed for speeding up the execution of array operations of the form C(c//0 plus cI) implied by A(a//0 plus al) OP B(b//0 plus bI), where a//0, a, b//0, b, c//0, c are
Banerjee, U., Gajski, D., Kuck, D.
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Compressive sensing for sparse arrays

2013 IEEE International Symposium on Phased Array Systems and Technology, 2013
We assess the usefulness of compressive sensing (CS) for processing signals from sparse or highly thinned receive arrays. Compressive sensing consists of a theory and related algorithms for solving under determined linear equations with the assumption that solutions have only a few non-zero or dominant values and the remaining values are zero or small.
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Sparse antenna arrays based on Costas arrays

Asia-Pacific Conference on Fundamental Problems of Opto- and Microelectronics 2017, 2019
Igor Anikin, Valery Sorokovikov
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A Robust Sparse Fractal Array

2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC), 2023
Kretika Goel, Monika Aggarwal, Subrat Kar   +2 more
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