Advanced cognitive networked radar surveillance

Mohammed Jahangir; Chris J. Baker; Michail Antoniou; Benjamin Griffin; Alessio Balleri; David Money; Stephen Harman

doi:10.1109/RadarConf2147009.2021.9455245

Advanced cognitive networked radar surveillance

Mohammed Jahangir, Chris J. Baker, Michail Antoniou, Benjamin Griffin, Alessio Balleri, David Money, Stephen Harman

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The concept of a traditional monostatic radar with co-located transmit and receive antennas naturally imposes performance limits that can adversely impact applications. Using a multiplicity of transmit and receive antennas and exploiting spatial diversity provides additional degrees of design freedom that can help overcome such limitations. Further, when coupled with cognitive signal processing, such advanced systems offer significant improvement in performance over their monostatic counterparts. This will also likely lead to new applications for radar sensing. In this paper we explore the fundamentals of multistatic network radar highlighting both potential and constraints whilst identifying future research needs and applications. Initial experimental results are presented for a 2-node networked staring radar.

Original language	English
Title of host publication	2021 IEEE Radar Conference (RadarConf21)
Subtitle of host publication	Radar on the Move
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781728176093
ISBN (Print)	9781728176109 (PoD)
DOIs	https://doi.org/10.1109/RadarConf2147009.2021.9455245
Publication status	Published - 18 Jun 2021
Event	2021 IEEE Radar Conference, RadarConf 2021 - Atlanta, United States Duration: 8 May 2021 → 14 May 2021

Publication series

Name	IEEE National Radar Conference - Proceedings
Publisher	IEEE
ISSN (Print)	1097-5659
ISSN (Electronic)	2375-5318

Conference

Conference	2021 IEEE Radar Conference, RadarConf 2021
Country/Territory	United States
City	Atlanta
Period	8/05/21 → 14/05/21

Bibliographical note

Funding Information:
The work was part funded by DSTL and supported by an Aveillant Limited funded Industrial PhD with Cranfield University. The authors would also like to thank Aveillant Limited for supporting the radar trials.

Keywords

Cognitive
Distributed
Intelligent
Multistatic
Networks
Radar

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/RadarConf2147009.2021.9455245Licence: None: All rights reserved

https://dspace.lib.cranfield.ac.uk/handle/1826/16798Licence: Creative Commons: Attribution-NonCommercial (CC BY-NC)

Cite this

Jahangir, M., Baker, C. J., Antoniou, M., Griffin, B., Balleri, A., Money, D., & Harman, S. (2021). Advanced cognitive networked radar surveillance. In 2021 IEEE Radar Conference (RadarConf21): Radar on the Move (pp. 1-6). Article 9455245 (IEEE National Radar Conference - Proceedings). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/RadarConf2147009.2021.9455245

@inproceedings{3b0c316461fc4a8fb477d7dd1513c0ee,

title = "Advanced cognitive networked radar surveillance",

abstract = "The concept of a traditional monostatic radar with co-located transmit and receive antennas naturally imposes performance limits that can adversely impact applications. Using a multiplicity of transmit and receive antennas and exploiting spatial diversity provides additional degrees of design freedom that can help overcome such limitations. Further, when coupled with cognitive signal processing, such advanced systems offer significant improvement in performance over their monostatic counterparts. This will also likely lead to new applications for radar sensing. In this paper we explore the fundamentals of multistatic network radar highlighting both potential and constraints whilst identifying future research needs and applications. Initial experimental results are presented for a 2-node networked staring radar.",

keywords = "Cognitive, Distributed, Intelligent, Multistatic, Networks, Radar",

author = "Mohammed Jahangir and Baker, {Chris J.} and Michail Antoniou and Benjamin Griffin and Alessio Balleri and David Money and Stephen Harman",

note = "Funding Information: The work was part funded by DSTL and supported by an Aveillant Limited funded Industrial PhD with Cranfield University. The authors would also like to thank Aveillant Limited for supporting the radar trials. ; 2021 IEEE Radar Conference, RadarConf 2021 ; Conference date: 08-05-2021 Through 14-05-2021",

year = "2021",

month = jun,

day = "18",

doi = "10.1109/RadarConf2147009.2021.9455245",

language = "English",

isbn = "9781728176109 (PoD)",

series = "IEEE National Radar Conference - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "1--6",

booktitle = "2021 IEEE Radar Conference (RadarConf21)",

}

Jahangir, M, Baker, CJ, Antoniou, M, Griffin, B, Balleri, A, Money, D & Harman, S 2021, Advanced cognitive networked radar surveillance. in 2021 IEEE Radar Conference (RadarConf21): Radar on the Move., 9455245, IEEE National Radar Conference - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), pp. 1-6, 2021 IEEE Radar Conference, RadarConf 2021, Atlanta, United States, 8/05/21. https://doi.org/10.1109/RadarConf2147009.2021.9455245

Advanced cognitive networked radar surveillance. / Jahangir, Mohammed; Baker, Chris J.; Antoniou, Michail et al.
2021 IEEE Radar Conference (RadarConf21): Radar on the Move. Institute of Electrical and Electronics Engineers (IEEE), 2021. p. 1-6 9455245 (IEEE National Radar Conference - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Advanced cognitive networked radar surveillance

AU - Jahangir, Mohammed

AU - Baker, Chris J.

AU - Antoniou, Michail

AU - Griffin, Benjamin

AU - Balleri, Alessio

AU - Money, David

AU - Harman, Stephen

N1 - Funding Information: The work was part funded by DSTL and supported by an Aveillant Limited funded Industrial PhD with Cranfield University. The authors would also like to thank Aveillant Limited for supporting the radar trials.

PY - 2021/6/18

Y1 - 2021/6/18

N2 - The concept of a traditional monostatic radar with co-located transmit and receive antennas naturally imposes performance limits that can adversely impact applications. Using a multiplicity of transmit and receive antennas and exploiting spatial diversity provides additional degrees of design freedom that can help overcome such limitations. Further, when coupled with cognitive signal processing, such advanced systems offer significant improvement in performance over their monostatic counterparts. This will also likely lead to new applications for radar sensing. In this paper we explore the fundamentals of multistatic network radar highlighting both potential and constraints whilst identifying future research needs and applications. Initial experimental results are presented for a 2-node networked staring radar.

AB - The concept of a traditional monostatic radar with co-located transmit and receive antennas naturally imposes performance limits that can adversely impact applications. Using a multiplicity of transmit and receive antennas and exploiting spatial diversity provides additional degrees of design freedom that can help overcome such limitations. Further, when coupled with cognitive signal processing, such advanced systems offer significant improvement in performance over their monostatic counterparts. This will also likely lead to new applications for radar sensing. In this paper we explore the fundamentals of multistatic network radar highlighting both potential and constraints whilst identifying future research needs and applications. Initial experimental results are presented for a 2-node networked staring radar.

KW - Cognitive

KW - Distributed

KW - Intelligent

KW - Multistatic

KW - Networks

KW - Radar

UR - http://www.scopus.com/inward/record.url?scp=85112473955&partnerID=8YFLogxK

U2 - 10.1109/RadarConf2147009.2021.9455245

DO - 10.1109/RadarConf2147009.2021.9455245

M3 - Conference contribution

AN - SCOPUS:85112473955

SN - 9781728176109 (PoD)

T3 - IEEE National Radar Conference - Proceedings

SP - 1

EP - 6

BT - 2021 IEEE Radar Conference (RadarConf21)

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2021 IEEE Radar Conference, RadarConf 2021

Y2 - 8 May 2021 through 14 May 2021

ER -

Advanced cognitive networked radar surveillance

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this