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

Steven Herbert; James Hopgood; Bernard Mulgrew

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

Steven Herbert, James Hopgood, Bernard Mulgrew

School of Engineering

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

Abstract / Description of output

This paper proposes a method for minimum mean squared error (MMSE) adaptive waveform design (AWD) in multiple-input-multiple-output (MIMO) active sensing systems which are used to track moving targets. The method proposed herein prompts two computational improvements compared to a related method for static targets. Consideration of moving targets also introduces the possibility of ‘model mismatch’ between the actual motion of the targets, and the model available to the MMSE AWD system. Results show that the proposed method leads to an improvement in mean squared error performance of up to 29% compared to the non-adaptive case.

Original language	English
Title of host publication	IEEE International Conference on Acoustics, Speech and Signal Processing
Publisher	Institute of Electrical and Electronics Engineers
Publication status	Accepted/In press - 15 Apr 2018

Keywords / Materials (for Non-textual outputs)

Adaptive waveform design
optimal design
MMSE
MIMO
active sensing

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 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
Optimality Criteria for Adaptive Waveform Design in MIMO Radar Systems
Herbert, S., Hopgood, J. & Mulgrew, B., 6 Dec 2017, Sensor Signal Processing for Defence. p. 11-15 5 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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

@inproceedings{c5affa6ce9b5453dab7e15cdeb34aad5,

title = "MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets",

abstract = "This paper proposes a method for minimum mean squared error (MMSE) adaptive waveform design (AWD) in multiple-input-multiple-output (MIMO) active sensing systems which are used to track moving targets. The method proposed herein prompts two computational improvements compared to a related method for static targets. Consideration of moving targets also introduces the possibility of {\textquoteleft}model mismatch{\textquoteright} between the actual motion of the targets, and the model available to the MMSE AWD system. Results show that the proposed method leads to an improvement in mean squared error performance of up to 29% compared to the non-adaptive case.",

keywords = "Adaptive waveform design, optimal design, MMSE, MIMO, active sensing",

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

year = "2018",

month = apr,

day = "15",

language = "English",

booktitle = "IEEE International Conference on Acoustics, Speech and Signal Processing",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

}

TY - GEN

T1 - MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets

AU - Herbert, Steven

AU - Hopgood, James

AU - Mulgrew, Bernard

PY - 2018/4/15

Y1 - 2018/4/15

N2 - This paper proposes a method for minimum mean squared error (MMSE) adaptive waveform design (AWD) in multiple-input-multiple-output (MIMO) active sensing systems which are used to track moving targets. The method proposed herein prompts two computational improvements compared to a related method for static targets. Consideration of moving targets also introduces the possibility of ‘model mismatch’ between the actual motion of the targets, and the model available to the MMSE AWD system. Results show that the proposed method leads to an improvement in mean squared error performance of up to 29% compared to the non-adaptive case.

AB - This paper proposes a method for minimum mean squared error (MMSE) adaptive waveform design (AWD) in multiple-input-multiple-output (MIMO) active sensing systems which are used to track moving targets. The method proposed herein prompts two computational improvements compared to a related method for static targets. Consideration of moving targets also introduces the possibility of ‘model mismatch’ between the actual motion of the targets, and the model available to the MMSE AWD system. Results show that the proposed method leads to an improvement in mean squared error performance of up to 29% compared to the non-adaptive case.

KW - Adaptive waveform design

KW - optimal design

KW - MMSE

KW - MIMO

KW - active sensing

M3 - Conference contribution

BT - IEEE International Conference on Acoustics, Speech and Signal Processing

PB - Institute of Electrical and Electronics Engineers

ER -

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

Abstract / Description of output

Keywords / Materials (for Non-textual outputs)

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 active sensing with applications to MIMO radar

Optimality Criteria for Adaptive Waveform Design in MIMO Radar Systems

Datasets

Software for "Approximate Adaptive Beam-Pattern Design"

Cite this