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Applications of Sensor Array and Multi-channel Signal Processing

A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT

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19 April 2018 - 9:35pm
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ICASSP2018_poster.pdf

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[1] , "A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3050. Accessed: Jun. 19, 2018.
@article{3050-18,
url = {http://sigport.org/3050},
author = { },
publisher = {IEEE SigPort},
title = {A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT},
year = {2018} }
TY - EJOUR
T1 - A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3050
ER -
. (2018). A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT. IEEE SigPort. http://sigport.org/3050
, 2018. A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT. Available at: http://sigport.org/3050.
. (2018). "A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT." Web.
1. . A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3050

Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar


The millimeter wave WLAN standard can be used for joint communication-radar by exploiting the waveform preamble as a radar pulse. The velocity estimation accuracy with this approach, however, is limited due to the short integration time. A physical increase in the radar pulse integration duration, however, leads to a decrease in the communication data rate.

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Authors:
Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr.
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21 April 2018 - 8:31pm
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Poster_VIRTUAL PULSE DESIGN FOR IEEE 802.11AD-BASED JOINT COMMUNICATION-RADAR.pdf

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[1] Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr., "Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2965. Accessed: Jun. 19, 2018.
@article{2965-18,
url = {http://sigport.org/2965},
author = {Preeti Kumari; Sergiy A. Vorobyov; and Robert W. Heath; Jr. },
publisher = {IEEE SigPort},
title = {Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar},
year = {2018} }
TY - EJOUR
T1 - Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar
AU - Preeti Kumari; Sergiy A. Vorobyov; and Robert W. Heath; Jr.
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2965
ER -
Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr.. (2018). Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar. IEEE SigPort. http://sigport.org/2965
Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr., 2018. Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar. Available at: http://sigport.org/2965.
Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr.. (2018). "Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar." Web.
1. Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr.. Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2965

JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK

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18 April 2018 - 8:05am
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FrankLIN_Presentation_Joint tracking and separation v3_pptx.pdf

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FrankLIN_Presentation_Joint tracking and separation v3_pptx.pdf

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[1] , "JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2806. Accessed: Jun. 19, 2018.
@article{2806-18,
url = {http://sigport.org/2806},
author = { },
publisher = {IEEE SigPort},
title = {JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK},
year = {2018} }
TY - EJOUR
T1 - JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2806
ER -
. (2018). JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK. IEEE SigPort. http://sigport.org/2806
, 2018. JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK. Available at: http://sigport.org/2806.
. (2018). "JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK." Web.
1. . JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2806

Joint Estimation of the Room Geometry and Modes with Compressed Sensing


Acoustical behavior of a room for a given position of microphone and sound source is usually described using the room impulse response. If we rely on the standard uniform sampling, the estimation of room impulse response for arbitrary positions in the room requires a large number of measurements. In order to lower the required sampling rate, some solutions have emerged that exploit the sparse representation of the room wavefield in the terms of plane waves in the low-frequency domain. The plane wave representation has a simple form in rectangular rooms.

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13 April 2018 - 10:07am
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Joint Estimation of the Room Geometry and Modes with Compressed Sensing.pdf

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[1] , "Joint Estimation of the Room Geometry and Modes with Compressed Sensing", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2708. Accessed: Jun. 19, 2018.
@article{2708-18,
url = {http://sigport.org/2708},
author = { },
publisher = {IEEE SigPort},
title = {Joint Estimation of the Room Geometry and Modes with Compressed Sensing},
year = {2018} }
TY - EJOUR
T1 - Joint Estimation of the Room Geometry and Modes with Compressed Sensing
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2708
ER -
. (2018). Joint Estimation of the Room Geometry and Modes with Compressed Sensing. IEEE SigPort. http://sigport.org/2708
, 2018. Joint Estimation of the Room Geometry and Modes with Compressed Sensing. Available at: http://sigport.org/2708.
. (2018). "Joint Estimation of the Room Geometry and Modes with Compressed Sensing." Web.
1. . Joint Estimation of the Room Geometry and Modes with Compressed Sensing [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2708

OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT


In this work, we consider the problem of synchronising separately located transmitters and a staring array receiver that also has a local transmitter. The acknowledged benefits of using separate transmitters in active sensing are often undermined by the difficulty in accurate synchronisation of the receiver and the transmitters. In this work, we propose a solution that is based on measurements from non-cooperative objects in the illuminated region. We formulate the problem as parameter estimation in a state space model with individual transmitter channel data cubes as measurements.

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Authors:
Kimin Kim, Murat Uney, Bernard Mulgrew
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15 April 2018 - 12:07am
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ICASSP_2018_Kimin_Kim_Poster

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[1] Kimin Kim, Murat Uney, Bernard Mulgrew, "OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2463. Accessed: Jun. 19, 2018.
@article{2463-18,
url = {http://sigport.org/2463},
author = {Kimin Kim; Murat Uney; Bernard Mulgrew },
publisher = {IEEE SigPort},
title = {OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT},
year = {2018} }
TY - EJOUR
T1 - OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT
AU - Kimin Kim; Murat Uney; Bernard Mulgrew
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2463
ER -
Kimin Kim, Murat Uney, Bernard Mulgrew. (2018). OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT. IEEE SigPort. http://sigport.org/2463
Kimin Kim, Murat Uney, Bernard Mulgrew, 2018. OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT. Available at: http://sigport.org/2463.
Kimin Kim, Murat Uney, Bernard Mulgrew. (2018). "OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT." Web.
1. Kimin Kim, Murat Uney, Bernard Mulgrew. OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2463

MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING


Seismic traces recorded in a single sensor from multiple shots demonstrate significant correlation. We propose a memory-assisted seismic signal compression method based on dictionary learning and sparse coding that would explore this correlation. Different from traditional methods, the dictionary used for compression is learned and updated by the information extracted from the common memory between the sender (sensor) node and the receiver node, over a fixed window of the most recent traces. The common memory is formed by the previously transmitted traces.

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Authors:
Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri
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10 November 2017 - 9:34am
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MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING

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[1] Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri, "MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2292. Accessed: Jun. 19, 2018.
@article{2292-17,
url = {http://sigport.org/2292},
author = {Xin Tian; Afshin Abdi; Entao Liu; Faramarz Fekri },
publisher = {IEEE SigPort},
title = {MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING},
year = {2017} }
TY - EJOUR
T1 - MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING
AU - Xin Tian; Afshin Abdi; Entao Liu; Faramarz Fekri
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2292
ER -
Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri. (2017). MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING. IEEE SigPort. http://sigport.org/2292
Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri, 2017. MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING. Available at: http://sigport.org/2292.
Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri. (2017). "MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING." Web.
1. Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri. MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2292

Distributionally Robust Chance-Constrained Minimum Variance Beamforming


Distributionally Robust Chance-Constrained Minimum Variance Beamforming

This paper studies distributionally robust chance-constrained minimum variance beamforming. In contrast to deterministic modeling of the steering vector, our approach models the uncertainty statistically via distributions. We select the weights that minimize the combined output power subject to the distributionally robust chance constraint that for all distributions in the uncertainty set, the gain should exceed unity with high probability.

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Authors:
Xiao Zhang, Qiang Feng, Ning Ge, Jianhua Lu
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23 March 2016 - 11:12am
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Slides.pdf

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[1] Xiao Zhang, Qiang Feng, Ning Ge, Jianhua Lu, "Distributionally Robust Chance-Constrained Minimum Variance Beamforming", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/996. Accessed: Jun. 19, 2018.
@article{996-16,
url = {http://sigport.org/996},
author = {Xiao Zhang; Qiang Feng; Ning Ge; Jianhua Lu },
publisher = {IEEE SigPort},
title = {Distributionally Robust Chance-Constrained Minimum Variance Beamforming},
year = {2016} }
TY - EJOUR
T1 - Distributionally Robust Chance-Constrained Minimum Variance Beamforming
AU - Xiao Zhang; Qiang Feng; Ning Ge; Jianhua Lu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/996
ER -
Xiao Zhang, Qiang Feng, Ning Ge, Jianhua Lu. (2016). Distributionally Robust Chance-Constrained Minimum Variance Beamforming. IEEE SigPort. http://sigport.org/996
Xiao Zhang, Qiang Feng, Ning Ge, Jianhua Lu, 2016. Distributionally Robust Chance-Constrained Minimum Variance Beamforming. Available at: http://sigport.org/996.
Xiao Zhang, Qiang Feng, Ning Ge, Jianhua Lu. (2016). "Distributionally Robust Chance-Constrained Minimum Variance Beamforming." Web.
1. Xiao Zhang, Qiang Feng, Ning Ge, Jianhua Lu. Distributionally Robust Chance-Constrained Minimum Variance Beamforming [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/996

Imaging in Radio Interferometry by Iterative Subset Scanning Using a Modified AMP Algorithm


Imaging techniques in radio interferometry often face a significant challenge posed by the large number of antenna signals received, from which the image information needs to be extracted. Beamforming is envisaged to reduce the rate required for transporting data from groups of antennas to a central site for further processing. We propose a novel method for image reconstruction based on the iterative scanning of a region of interest, combined with randomized beamforming. A modified approximate message-passing algorithm

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Authors:
Paul Hurley, Matthieu Simeoni, Sanaz Kazemi
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19 March 2016 - 10:22am
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ICASSP_2016_poster_v1_A0.pdf

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[1] Paul Hurley, Matthieu Simeoni, Sanaz Kazemi, "Imaging in Radio Interferometry by Iterative Subset Scanning Using a Modified AMP Algorithm", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/813. Accessed: Jun. 19, 2018.
@article{813-16,
url = {http://sigport.org/813},
author = {Paul Hurley; Matthieu Simeoni; Sanaz Kazemi },
publisher = {IEEE SigPort},
title = {Imaging in Radio Interferometry by Iterative Subset Scanning Using a Modified AMP Algorithm},
year = {2016} }
TY - EJOUR
T1 - Imaging in Radio Interferometry by Iterative Subset Scanning Using a Modified AMP Algorithm
AU - Paul Hurley; Matthieu Simeoni; Sanaz Kazemi
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/813
ER -
Paul Hurley, Matthieu Simeoni, Sanaz Kazemi. (2016). Imaging in Radio Interferometry by Iterative Subset Scanning Using a Modified AMP Algorithm. IEEE SigPort. http://sigport.org/813
Paul Hurley, Matthieu Simeoni, Sanaz Kazemi, 2016. Imaging in Radio Interferometry by Iterative Subset Scanning Using a Modified AMP Algorithm. Available at: http://sigport.org/813.
Paul Hurley, Matthieu Simeoni, Sanaz Kazemi. (2016). "Imaging in Radio Interferometry by Iterative Subset Scanning Using a Modified AMP Algorithm." Web.
1. Paul Hurley, Matthieu Simeoni, Sanaz Kazemi. Imaging in Radio Interferometry by Iterative Subset Scanning Using a Modified AMP Algorithm [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/813

Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging


In this talk, we present a new time domain electromagnetic tomographic imaging algorithm using coded
multiple excitation signals to reconstruct an extended object immersed in inhomogeneous medium. Three waveform encoding
techniques are developed to enable simultaneous source excitation as a way of improving computational efficiency

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Authors:
Chengdong Cheng, Enyue Lu
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23 February 2016 - 1:44pm
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GlobalSIP2015_2.pdf

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[1] Chengdong Cheng, Enyue Lu, "Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/542. Accessed: Jun. 19, 2018.
@article{542-15,
url = {http://sigport.org/542},
author = {Chengdong Cheng; Enyue Lu },
publisher = {IEEE SigPort},
title = {Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging},
year = {2015} }
TY - EJOUR
T1 - Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging
AU - Chengdong Cheng; Enyue Lu
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/542
ER -
Chengdong Cheng, Enyue Lu. (2015). Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging. IEEE SigPort. http://sigport.org/542
Chengdong Cheng, Enyue Lu, 2015. Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging. Available at: http://sigport.org/542.
Chengdong Cheng, Enyue Lu. (2015). "Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging." Web.
1. Chengdong Cheng, Enyue Lu. Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/542