Results 241 to 250 of about 269,186 (284)

Direct-MUSIC on sparse arrays

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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Sparse Optical Phased Array Design

2019 IEEE 16th International Conference on Group IV Photonics (GFP), 2019
We propose a scalable, low fill factor, optical phased array design based on sparse arrays, relaxing the sub-wavelength antenna pitch requirement for sidelobe suppression, achieving significantly lower beamsteering power consumption than a uniform array.
Francis Smith, Wuxiucheng Wang, Hui Wu
openaire   +1 more source

Autofocus for sparse array imaging

SPIE Proceedings, 2010
If sparse arrays are attached to structures for the purposes of structural health monitoring it is likely that there will be variation in the placement of the sensors, resulting in deviation from the assumed locations. In addition, poor knowledge of the material through which the signals are propagating can result in the use of incorrect velocities ...
Anthony J. Croxford, Alan J. Hunter
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Sparse sensing with coprime arrays

2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, 2010
Coprime sampling has, in the past, been used for signal processing applications such as range and doppler improvement in radar, and for identifying sinusoids in noise. This paper considers a coprime pair of samplers in space or time from the point of view of the difference coarray, which is key to the increased freedom available for processing with ...
P. P. Vaidyanathan, Piya Pal
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Bilinear problems and sparse arrays

The Journal of the Acoustical Society of America, 2017
Inverse problems in imaging with sensor arrays often involve estimation of desired parameters (associated with targets or sources) in presence of undesired quantities such as modeling and calibration errors, or uncertainties in accurate modeling of the propagation medium.
Ali Koochakzadeh, Piya Pal
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Sparse Arrays for SatCom Applications

31st AIAA International Communications Satellite Systems Conference, 2013
The paper provides a short overview on recent ESA developments on array antenna architectures for satellite antennas generating a multiple spot beams coverage with a single aperture. In particular, solutions based on direct radiating arrays, discrete lens arrays, and arrays magnified by confocal reflectors will be discussed.
Piero Angeletti, Giovanni Toso
openaire   +1 more source

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
openaire   +1 more source