Optimality Criteria for Adaptive Waveform Design in MIMO Radar Systems

Steven Herbert; James Hopgood; Bernard Mulgrew

Optimality Criteria for Adaptive Waveform Design in MIMO Radar Systems

Steven Herbert, James Hopgood, Bernard Mulgrew

School of Engineering

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

Abstract

Adaptive waveform design in MIMO radar can improve the estimation of target parameters. Comparing the relative benefits of known optimality criteria, namely the A-optimal, D-optimal and E-optimal criteria, is important to inform the best implementation of actual MIMO radar adaptive waveform design systems. In this paper we provide such a comparison, both theoretically and by assessing simulated numerical results. Whilst all three criteria are complementary, and thus all potentially could have a role in adaptive waveform design for MIMO radar, our results indicate that a system which generally uses A-optimal design, but switches to E-optimal design in some circumstances may be suitable for practical application.

Original language	English
Title of host publication	Sensor Signal Processing for Defence
Pages	11-15
Number of pages	5
Publication status	Published - 6 Dec 2017

1 Finished

Signal Processing in the Networked Battlespace
Mulgrew, B., Davies, M., Hopgood, J. & Thompson, J.
EPSRC
1/04/13 → 30/06/18
Project: Research

2 Article
1 Conference contribution

Computationally simple MMSE (A-optimal) Adaptive Beam-pattern Design for MIMO Active Sensing Systems via a Linear-Gaussian Approximation
Herbert, S., Hopgood, J. R. & Mulgrew, B., 15 Sept 2018, In: IEEE Transactions on Signal Processing. 66, 18, p. 4935 - 4945 11 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets
Herbert, S., Hopgood, J. & Mulgrew, B., 15 Apr 2018, (Accepted/In press) IEEE International Conference on Acoustics, Speech and Signal Processing. Institute of Electrical and Electronics Engineers
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
MMSE adaptive waveform design for active sensing with applications to MIMO radar
Herbert, S., Hopgood, J. & Mulgrew, B., 1 Mar 2018, In: IEEE Transactions on Signal Processing. 66, 5, p. 1361 - 1373
Research output: Contribution to journal › Article › peer-review

Open Access
File

Software for "Approximate Adaptive Beam-Pattern Design"
Herbert, S. (Creator), Hopgood, J. (Supervisor) & Mulgrew, B. (Supervisor), Edinburgh DataShare, 3 Aug 2018
DOI: 10.7488/ds/2403
Dataset

Cite this

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title = "Optimality Criteria for Adaptive Waveform Design in MIMO Radar Systems",

abstract = "Adaptive waveform design in MIMO radar can improve the estimation of target parameters. Comparing the relative benefits of known optimality criteria, namely the A-optimal, D-optimal and E-optimal criteria, is important to inform the best implementation of actual MIMO radar adaptive waveform design systems. In this paper we provide such a comparison, both theoretically and by assessing simulated numerical results. Whilst all three criteria are complementary, and thus all potentially could have a role in adaptive waveform design for MIMO radar, our results indicate that a system which generally uses A-optimal design, but switches to E-optimal design in some circumstances may be suitable for practical application.",

author = "Steven Herbert and James Hopgood and Bernard Mulgrew",

year = "2017",

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pages = "11--15",

booktitle = "Sensor Signal Processing for Defence",

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T1 - Optimality Criteria for Adaptive Waveform Design in MIMO Radar Systems

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AU - Hopgood, James

AU - Mulgrew, Bernard

PY - 2017/12/6

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N2 - Adaptive waveform design in MIMO radar can improve the estimation of target parameters. Comparing the relative benefits of known optimality criteria, namely the A-optimal, D-optimal and E-optimal criteria, is important to inform the best implementation of actual MIMO radar adaptive waveform design systems. In this paper we provide such a comparison, both theoretically and by assessing simulated numerical results. Whilst all three criteria are complementary, and thus all potentially could have a role in adaptive waveform design for MIMO radar, our results indicate that a system which generally uses A-optimal design, but switches to E-optimal design in some circumstances may be suitable for practical application.

AB - Adaptive waveform design in MIMO radar can improve the estimation of target parameters. Comparing the relative benefits of known optimality criteria, namely the A-optimal, D-optimal and E-optimal criteria, is important to inform the best implementation of actual MIMO radar adaptive waveform design systems. In this paper we provide such a comparison, both theoretically and by assessing simulated numerical results. Whilst all three criteria are complementary, and thus all potentially could have a role in adaptive waveform design for MIMO radar, our results indicate that a system which generally uses A-optimal design, but switches to E-optimal design in some circumstances may be suitable for practical application.

M3 - Conference contribution

SP - 11

EP - 15

BT - Sensor Signal Processing for Defence

ER -

Optimality Criteria for Adaptive Waveform Design in MIMO Radar Systems

Abstract

Fingerprint

Projects

Signal Processing in the Networked Battlespace

Research output

Computationally simple MMSE (A-optimal) Adaptive Beam-pattern Design for MIMO Active Sensing Systems via a Linear-Gaussian Approximation

MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets

MMSE adaptive waveform design for active sensing with applications to MIMO radar

Datasets

Software for "Approximate Adaptive Beam-Pattern Design"

Cite this