Abstract

We provide an overview of recent work on distributed and agile sensing algorithms and their implementation. Modern sensor systems with embedded processing can allow for distributed sensing to continuously infer intelligent information as well as for agile sensing to configure systems in order to maintain a desirable performance level. We examine distributed inference techniques for detection and estimation at the fusion center and wireless networks for the sensor systems for real time scenarios. We also study waveform-agile sensing, which includes methods for adapting the sensor transmit waveform to match the environment and to optimize the selected performance metric. We specifically concentrate on radar and underwater acoustic signal transmission environments. As we consider systems with potentially large number of sensors, we discuss the use of resource-agile implementation approaches based on multiple-core processors in order to efficiently implement the computationally intensive processing in configuring the sensors. These resource-agile approaches can be extended to also optimize sensing in distributed sensor networks.

Original languageEnglish (US)
Pages (from-to)1-14
Number of pages14
JournalDigital Signal Processing: A Review Journal
Volume39
DOIs
StatePublished - Apr 1 2015

Fingerprint

Sensors
Underwater acoustics
Processing
Sensor networks
Wireless networks
Radar
Fusion reactions

Keywords

  • Agile sensing
  • Distributed inference
  • Distributed sensing
  • Resource-agile processing
  • Sensor networks
  • Smart grid

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

An overview of recent advances on distributed and agile sensing algorithms and implementation. / Banavar, Mahesh K.; Zhang, Jun J.; Chakraborty, Bhavana; Kwon, Homin; Li, Ying; Jiang, Huaiguang; Spanias, Andreas; Tepedelenlioglu, Cihan; Chakrabarti, Chaitali; Papandreou-Suppappola, Antonia.

In: Digital Signal Processing: A Review Journal, Vol. 39, 01.04.2015, p. 1-14.

Research output: Contribution to journalArticle

@article{48ea34f3bf6942888663738fa38968f2,
title = "An overview of recent advances on distributed and agile sensing algorithms and implementation",
abstract = "We provide an overview of recent work on distributed and agile sensing algorithms and their implementation. Modern sensor systems with embedded processing can allow for distributed sensing to continuously infer intelligent information as well as for agile sensing to configure systems in order to maintain a desirable performance level. We examine distributed inference techniques for detection and estimation at the fusion center and wireless networks for the sensor systems for real time scenarios. We also study waveform-agile sensing, which includes methods for adapting the sensor transmit waveform to match the environment and to optimize the selected performance metric. We specifically concentrate on radar and underwater acoustic signal transmission environments. As we consider systems with potentially large number of sensors, we discuss the use of resource-agile implementation approaches based on multiple-core processors in order to efficiently implement the computationally intensive processing in configuring the sensors. These resource-agile approaches can be extended to also optimize sensing in distributed sensor networks.",
keywords = "Agile sensing, Distributed inference, Distributed sensing, Resource-agile processing, Sensor networks, Smart grid",
author = "Banavar, {Mahesh K.} and Zhang, {Jun J.} and Bhavana Chakraborty and Homin Kwon and Ying Li and Huaiguang Jiang and Andreas Spanias and Cihan Tepedelenlioglu and Chaitali Chakrabarti and Antonia Papandreou-Suppappola",
year = "2015",
month = "4",
day = "1",
doi = "10.1016/j.dsp.2015.01.001",
language = "English (US)",
volume = "39",
pages = "1--14",
journal = "Digital Signal Processing: A Review Journal",
issn = "1051-2004",
publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - An overview of recent advances on distributed and agile sensing algorithms and implementation

AU - Banavar, Mahesh K.

AU - Zhang, Jun J.

AU - Chakraborty, Bhavana

AU - Kwon, Homin

AU - Li, Ying

AU - Jiang, Huaiguang

AU - Spanias, Andreas

AU - Tepedelenlioglu, Cihan

AU - Chakrabarti, Chaitali

AU - Papandreou-Suppappola, Antonia

PY - 2015/4/1

Y1 - 2015/4/1

N2 - We provide an overview of recent work on distributed and agile sensing algorithms and their implementation. Modern sensor systems with embedded processing can allow for distributed sensing to continuously infer intelligent information as well as for agile sensing to configure systems in order to maintain a desirable performance level. We examine distributed inference techniques for detection and estimation at the fusion center and wireless networks for the sensor systems for real time scenarios. We also study waveform-agile sensing, which includes methods for adapting the sensor transmit waveform to match the environment and to optimize the selected performance metric. We specifically concentrate on radar and underwater acoustic signal transmission environments. As we consider systems with potentially large number of sensors, we discuss the use of resource-agile implementation approaches based on multiple-core processors in order to efficiently implement the computationally intensive processing in configuring the sensors. These resource-agile approaches can be extended to also optimize sensing in distributed sensor networks.

AB - We provide an overview of recent work on distributed and agile sensing algorithms and their implementation. Modern sensor systems with embedded processing can allow for distributed sensing to continuously infer intelligent information as well as for agile sensing to configure systems in order to maintain a desirable performance level. We examine distributed inference techniques for detection and estimation at the fusion center and wireless networks for the sensor systems for real time scenarios. We also study waveform-agile sensing, which includes methods for adapting the sensor transmit waveform to match the environment and to optimize the selected performance metric. We specifically concentrate on radar and underwater acoustic signal transmission environments. As we consider systems with potentially large number of sensors, we discuss the use of resource-agile implementation approaches based on multiple-core processors in order to efficiently implement the computationally intensive processing in configuring the sensors. These resource-agile approaches can be extended to also optimize sensing in distributed sensor networks.

KW - Agile sensing

KW - Distributed inference

KW - Distributed sensing

KW - Resource-agile processing

KW - Sensor networks

KW - Smart grid

UR - http://www.scopus.com/inward/record.url?scp=84924541975&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84924541975&partnerID=8YFLogxK

U2 - 10.1016/j.dsp.2015.01.001

DO - 10.1016/j.dsp.2015.01.001

M3 - Article

AN - SCOPUS:84924541975

VL - 39

SP - 1

EP - 14

JO - Digital Signal Processing: A Review Journal

JF - Digital Signal Processing: A Review Journal

SN - 1051-2004

ER -