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Sensor Array Processing

Sample Space-Time Covariance Estimation

Connor Delaosa

Estimation errors are incurred when calculating the sample space-time covariance matrix. We formulate the variance of this estimator when operating on a finite sample set, compare it to known results, and demonstrate its precision in simulations. The variance of the estimation links directly to previously explored perturbation of the analytic eigenvalues and eigenspaces of a parahermitian cross-spectral density matrix when estimated from finite data.

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Authors:
Connor Delaosa
Connor Delaosa, Jennifer Pestana, Nicholas J. Goddard, Sam Somasundaram, Stephan Weiss
Submitted On:
15 May 2019 - 4:53pm
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icassp_2a.pdf

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[1] Connor Delaosa, Jennifer Pestana, Nicholas J. Goddard, Sam Somasundaram, Stephan Weiss, "Sample Space-Time Covariance Estimation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4531. Accessed: Oct. 14, 2019.
@article{4531-19,
url = {http://sigport.org/4531},
author = {Connor Delaosa; Jennifer Pestana; Nicholas J. Goddard; Sam Somasundaram; Stephan Weiss },
publisher = {IEEE SigPort},
title = {Sample Space-Time Covariance Estimation},
year = {2019} }
TY - EJOUR
T1 - Sample Space-Time Covariance Estimation
AU - Connor Delaosa; Jennifer Pestana; Nicholas J. Goddard; Sam Somasundaram; Stephan Weiss
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4531
ER -
Connor Delaosa, Jennifer Pestana, Nicholas J. Goddard, Sam Somasundaram, Stephan Weiss. (2019). Sample Space-Time Covariance Estimation. IEEE SigPort. http://sigport.org/4531
Connor Delaosa, Jennifer Pestana, Nicholas J. Goddard, Sam Somasundaram, Stephan Weiss, 2019. Sample Space-Time Covariance Estimation. Available at: http://sigport.org/4531.
Connor Delaosa, Jennifer Pestana, Nicholas J. Goddard, Sam Somasundaram, Stephan Weiss. (2019). "Sample Space-Time Covariance Estimation." Web.
1. Connor Delaosa, Jennifer Pestana, Nicholas J. Goddard, Sam Somasundaram, Stephan Weiss. Sample Space-Time Covariance Estimation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4531

Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot

Anupama Govinda Raj

We address the problem of search-free DOA estimation from a single noisy snapshot for sensor arrays of arbitrary geometry, by extending a method of gridless super-resolution beam-forming to arbitrary arrays with noisy measurements. The primal atomic norm minimization problem is converted to a dual problem in which the periodic dual function is represented with a trigonometric polynomial using truncated Fourier series. The number of terms required for accurate representation depends linearly on the distance of the farthest sensor from a reference.

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Authors:
Anupama Govinda Raj
Anupama Govinda Raj, James H. McClellan*
Submitted On:
10 May 2019 - 6:07pm
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ICASSP_Slides_SuperRes_DOA.pdf

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[1] Anupama Govinda Raj, James H. McClellan*, "Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4414. Accessed: Oct. 14, 2019.
@article{4414-19,
url = {http://sigport.org/4414},
author = {Anupama Govinda Raj; James H. McClellan* },
publisher = {IEEE SigPort},
title = {Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot},
year = {2019} }
TY - EJOUR
T1 - Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot
AU - Anupama Govinda Raj; James H. McClellan*
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4414
ER -
Anupama Govinda Raj, James H. McClellan*. (2019). Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot. IEEE SigPort. http://sigport.org/4414
Anupama Govinda Raj, James H. McClellan*, 2019. Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot. Available at: http://sigport.org/4414.
Anupama Govinda Raj, James H. McClellan*. (2019). "Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot." Web.
1. Anupama Govinda Raj, James H. McClellan*. Super-Resolution DOA Estimation for Arbitrary Array Geometries Using a Single Noisy Snapshot [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4414

3D Coprime Arrays in Sparse Sensing

Conghui Li

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Authors:
Conghui Li
Conghui Li, Lu Gan, Cong Ling
Submitted On:
9 May 2019 - 6:08am
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icassp_s09.pdf

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[1] Conghui Li, Lu Gan, Cong Ling, "3D Coprime Arrays in Sparse Sensing", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4181. Accessed: Oct. 14, 2019.
@article{4181-19,
url = {http://sigport.org/4181},
author = {Conghui Li; Lu Gan; Cong Ling },
publisher = {IEEE SigPort},
title = {3D Coprime Arrays in Sparse Sensing},
year = {2019} }
TY - EJOUR
T1 - 3D Coprime Arrays in Sparse Sensing
AU - Conghui Li; Lu Gan; Cong Ling
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4181
ER -
Conghui Li, Lu Gan, Cong Ling. (2019). 3D Coprime Arrays in Sparse Sensing. IEEE SigPort. http://sigport.org/4181
Conghui Li, Lu Gan, Cong Ling, 2019. 3D Coprime Arrays in Sparse Sensing. Available at: http://sigport.org/4181.
Conghui Li, Lu Gan, Cong Ling. (2019). "3D Coprime Arrays in Sparse Sensing." Web.
1. Conghui Li, Lu Gan, Cong Ling. 3D Coprime Arrays in Sparse Sensing [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4181

Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring

Patrick Wijnings

Poster for "Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring".
https://ieeexplore.ieee.org/document/8682835

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Authors:
Patrick Wijnings
Patrick W.A. Wijnings, Sander Stuijk, Bert de Vries, Henk Corporaal
Submitted On:
8 May 2019 - 10:14am
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[1] Patrick W.A. Wijnings, Sander Stuijk, Bert de Vries, Henk Corporaal, "Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4115. Accessed: Oct. 14, 2019.
@article{4115-19,
url = {http://sigport.org/4115},
author = {Patrick W.A. Wijnings; Sander Stuijk; Bert de Vries; Henk Corporaal },
publisher = {IEEE SigPort},
title = {Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring},
year = {2019} }
TY - EJOUR
T1 - Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring
AU - Patrick W.A. Wijnings; Sander Stuijk; Bert de Vries; Henk Corporaal
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4115
ER -
Patrick W.A. Wijnings, Sander Stuijk, Bert de Vries, Henk Corporaal. (2019). Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring. IEEE SigPort. http://sigport.org/4115
Patrick W.A. Wijnings, Sander Stuijk, Bert de Vries, Henk Corporaal, 2019. Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring. Available at: http://sigport.org/4115.
Patrick W.A. Wijnings, Sander Stuijk, Bert de Vries, Henk Corporaal. (2019). "Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring." Web.
1. Patrick W.A. Wijnings, Sander Stuijk, Bert de Vries, Henk Corporaal. Robust Bayesian Beamforming for Sources at Different Distances with Applications in Urban Monitoring [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4115

AN LS LOCALISATION METHOD FOR MASSIVE MIMO TRANSMISSION SYSTEMS

Markus Rupp

We present a novel localization method based on directional beams,
as available in novel massive MIMO transmission techniques instead
of radius information, and derive a least squares (LS) estimation
method. The new method is a direct LS method that can be solved by
a linear set of equations rather than an iterative method required for
radius information. In a further step, we also show how to transform
radius information into virtual beams to apply the proposed method.
Finally, we evaluate the accuracy of the new methods by simulations.

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Authors:
Markus Rupp
Markus Rupp, Stefan Schwarz
Submitted On:
8 May 2019 - 5:31am
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[1] Markus Rupp, Stefan Schwarz, "AN LS LOCALISATION METHOD FOR MASSIVE MIMO TRANSMISSION SYSTEMS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4057. Accessed: Oct. 14, 2019.
@article{4057-19,
url = {http://sigport.org/4057},
author = {Markus Rupp; Stefan Schwarz },
publisher = {IEEE SigPort},
title = {AN LS LOCALISATION METHOD FOR MASSIVE MIMO TRANSMISSION SYSTEMS},
year = {2019} }
TY - EJOUR
T1 - AN LS LOCALISATION METHOD FOR MASSIVE MIMO TRANSMISSION SYSTEMS
AU - Markus Rupp; Stefan Schwarz
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4057
ER -
Markus Rupp, Stefan Schwarz. (2019). AN LS LOCALISATION METHOD FOR MASSIVE MIMO TRANSMISSION SYSTEMS. IEEE SigPort. http://sigport.org/4057
Markus Rupp, Stefan Schwarz, 2019. AN LS LOCALISATION METHOD FOR MASSIVE MIMO TRANSMISSION SYSTEMS. Available at: http://sigport.org/4057.
Markus Rupp, Stefan Schwarz. (2019). "AN LS LOCALISATION METHOD FOR MASSIVE MIMO TRANSMISSION SYSTEMS." Web.
1. Markus Rupp, Stefan Schwarz. AN LS LOCALISATION METHOD FOR MASSIVE MIMO TRANSMISSION SYSTEMS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4057

Inferring Private Information in Wireless Sensor Networks

Jemin George

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Authors:
Jemin George
Submitted On:
7 May 2019 - 5:51pm
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ICASSP_paper3565.pdf

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[1] , "Inferring Private Information in Wireless Sensor Networks", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3963. Accessed: Oct. 14, 2019.
@article{3963-19,
url = {http://sigport.org/3963},
author = { },
publisher = {IEEE SigPort},
title = {Inferring Private Information in Wireless Sensor Networks},
year = {2019} }
TY - EJOUR
T1 - Inferring Private Information in Wireless Sensor Networks
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3963
ER -
. (2019). Inferring Private Information in Wireless Sensor Networks. IEEE SigPort. http://sigport.org/3963
, 2019. Inferring Private Information in Wireless Sensor Networks. Available at: http://sigport.org/3963.
. (2019). "Inferring Private Information in Wireless Sensor Networks." Web.
1. . Inferring Private Information in Wireless Sensor Networks [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3963

Toeplitz Matrix Completion for Direction Finding Using a Modified Nested Linear Array

huiping huang

A modified nested linear array (MNLA) has been reported recently for a greater potential in increasing the degree-of-freedom. However, there exist some “holes” in the difference co-array, which results in missing “lags” and limited performance of direction-of-arrival (DOA) estimation. In order to tackle this problem, this paper applies a Toeplitz matrix completion technique to MNLA, and investigates the performance of DOA estimation on this basis. Particularly, a semidefinite program with trace minimization is derived to obtain the covariance matrix with Hermitian and Toeplitz structure.

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Authors:
huiping huang
Huiping Huang, Yang Miao, Yi Gong, Bin Liao
Submitted On:
7 May 2019 - 2:14pm
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Poster of ICASSP Paper#2290

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[1] Huiping Huang, Yang Miao, Yi Gong, Bin Liao, "Toeplitz Matrix Completion for Direction Finding Using a Modified Nested Linear Array", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3936. Accessed: Oct. 14, 2019.
@article{3936-19,
url = {http://sigport.org/3936},
author = {Huiping Huang; Yang Miao; Yi Gong; Bin Liao },
publisher = {IEEE SigPort},
title = {Toeplitz Matrix Completion for Direction Finding Using a Modified Nested Linear Array},
year = {2019} }
TY - EJOUR
T1 - Toeplitz Matrix Completion for Direction Finding Using a Modified Nested Linear Array
AU - Huiping Huang; Yang Miao; Yi Gong; Bin Liao
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3936
ER -
Huiping Huang, Yang Miao, Yi Gong, Bin Liao. (2019). Toeplitz Matrix Completion for Direction Finding Using a Modified Nested Linear Array. IEEE SigPort. http://sigport.org/3936
Huiping Huang, Yang Miao, Yi Gong, Bin Liao, 2019. Toeplitz Matrix Completion for Direction Finding Using a Modified Nested Linear Array. Available at: http://sigport.org/3936.
Huiping Huang, Yang Miao, Yi Gong, Bin Liao. (2019). "Toeplitz Matrix Completion for Direction Finding Using a Modified Nested Linear Array." Web.
1. Huiping Huang, Yang Miao, Yi Gong, Bin Liao. Toeplitz Matrix Completion for Direction Finding Using a Modified Nested Linear Array [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3936

Alternating Projections based Gridless DoA Estimation (Poster)

Mark Wagner

Paper Details

Authors:
Mark Wagner
Mark Wagner, Yongsung Park, Peter Gerstoft
Submitted On:
7 May 2019 - 1:30pm
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Alternating Projections based Gridless DoA Estimation (ICASSP 2019 Poster)

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[1] Mark Wagner, Yongsung Park, Peter Gerstoft, "Alternating Projections based Gridless DoA Estimation (Poster)", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3931. Accessed: Oct. 14, 2019.
@article{3931-19,
url = {http://sigport.org/3931},
author = {Mark Wagner; Yongsung Park; Peter Gerstoft },
publisher = {IEEE SigPort},
title = {Alternating Projections based Gridless DoA Estimation (Poster)},
year = {2019} }
TY - EJOUR
T1 - Alternating Projections based Gridless DoA Estimation (Poster)
AU - Mark Wagner; Yongsung Park; Peter Gerstoft
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3931
ER -
Mark Wagner, Yongsung Park, Peter Gerstoft. (2019). Alternating Projections based Gridless DoA Estimation (Poster). IEEE SigPort. http://sigport.org/3931
Mark Wagner, Yongsung Park, Peter Gerstoft, 2019. Alternating Projections based Gridless DoA Estimation (Poster). Available at: http://sigport.org/3931.
Mark Wagner, Yongsung Park, Peter Gerstoft. (2019). "Alternating Projections based Gridless DoA Estimation (Poster)." Web.
1. Mark Wagner, Yongsung Park, Peter Gerstoft. Alternating Projections based Gridless DoA Estimation (Poster) [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3931

Subspace-Based Imaging Using Only Power Measurements

Belal Korany

In this paper, we are interested in the high-resolution
imaging of an unknown area based on only power measurements
of a small number of wireless transceivers located on one
side of the unknown area. In order to do so, we propose a
framework that achieves a polynomial order reduction in the
number of antennas required for high-resolution imaging. More
specifically, we show that by spacing the antennas at multiples
of the wavelength and applying subspace-based analysis, we can
image M targets using only 2M+1 transmit/receive antennas (as

Paper Details

Authors:
Belal Korany
Saandeep Depatla, Yasamin Mostofi
Submitted On:
9 July 2018 - 5:24pm
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KoranyDepatlaMostofi_SAM18_poster.pdf

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[1] Saandeep Depatla, Yasamin Mostofi, "Subspace-Based Imaging Using Only Power Measurements", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3376. Accessed: Oct. 14, 2019.
@article{3376-18,
url = {http://sigport.org/3376},
author = {Saandeep Depatla; Yasamin Mostofi },
publisher = {IEEE SigPort},
title = {Subspace-Based Imaging Using Only Power Measurements},
year = {2018} }
TY - EJOUR
T1 - Subspace-Based Imaging Using Only Power Measurements
AU - Saandeep Depatla; Yasamin Mostofi
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3376
ER -
Saandeep Depatla, Yasamin Mostofi. (2018). Subspace-Based Imaging Using Only Power Measurements. IEEE SigPort. http://sigport.org/3376
Saandeep Depatla, Yasamin Mostofi, 2018. Subspace-Based Imaging Using Only Power Measurements. Available at: http://sigport.org/3376.
Saandeep Depatla, Yasamin Mostofi. (2018). "Subspace-Based Imaging Using Only Power Measurements." Web.
1. Saandeep Depatla, Yasamin Mostofi. Subspace-Based Imaging Using Only Power Measurements [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3376

Symmetric Sparse Linear Array for Active Imaging

Robin Rajamaki

Sparse sensor arrays can achieve significantly more degrees of freedom than the number of elements by leveraging the co-array, a virtual structure that arises from the far field narrowband signal model. Although several sparse array configurations have been developed for passive sensing tasks, less attention has been paid to arrays suitable for active sensing. This paper presents a novel active sparse linear array, called the Interleaved Wichmann Array (IWA). The IWA only has a few closely spaced elements, which may make it more robust to mutual coupling effects.

Paper Details

Authors:
Robin Rajamaki
Visa Koivunen
Submitted On:
8 July 2018 - 5:20am
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sam_slides.pdf

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[1] Visa Koivunen, "Symmetric Sparse Linear Array for Active Imaging", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3371. Accessed: Oct. 14, 2019.
@article{3371-18,
url = {http://sigport.org/3371},
author = {Visa Koivunen },
publisher = {IEEE SigPort},
title = {Symmetric Sparse Linear Array for Active Imaging},
year = {2018} }
TY - EJOUR
T1 - Symmetric Sparse Linear Array for Active Imaging
AU - Visa Koivunen
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3371
ER -
Visa Koivunen. (2018). Symmetric Sparse Linear Array for Active Imaging. IEEE SigPort. http://sigport.org/3371
Visa Koivunen, 2018. Symmetric Sparse Linear Array for Active Imaging. Available at: http://sigport.org/3371.
Visa Koivunen. (2018). "Symmetric Sparse Linear Array for Active Imaging." Web.
1. Visa Koivunen. Symmetric Sparse Linear Array for Active Imaging [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3371

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