Performance analysis of a persymmetric adaptive matched filter

Jun Liu; Hongbin Li; Braham Himed

doi:10.1109/SAM.2016.7569617

Performance analysis of a persymmetric adaptive matched filter

Jun Liu, Hongbin Li, Braham Himed

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

Abstract

We examine the adaptive detection problem in the presence of colored noise with an unknown covariance matrix, by exploiting a persymmetric structure in the received signal. The persymmetric adaptive matched filter (PS-AMF) is used to address this problem, which can significantly alleviate the requirement of secondary data. In this paper, finite-sum expressions for the probability of false alarm of the PS-AMF are derived, which are more convenient to use in calculating the detection threshold. Moreover, the detection probabilities of the PS-AMF are derived. These theoretical results are all confirmed using Monte Carlo simulations.

Original language	English
Title of host publication	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016
ISBN (Electronic)	9781509021031
DOIs	https://doi.org/10.1109/SAM.2016.7569617
State	Published - 15 Sep 2016
Event	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016 - Rio de Rio de Janeiro, Brazil Duration: 10 Jul 2016 → 13 Jul 2016

Publication series

Name	Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
Volume	2016-September
ISSN (Electronic)	2151-870X

Conference

Conference	2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016
Country/Territory	Brazil
City	Rio de Rio de Janeiro
Period	10/07/16 → 13/07/16

Keywords

Adaptive matched filter
Laplace approximation
Persymmetric
adaptive detection

Access to Document

10.1109/SAM.2016.7569617

Cite this

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title = "Performance analysis of a persymmetric adaptive matched filter",

abstract = "We examine the adaptive detection problem in the presence of colored noise with an unknown covariance matrix, by exploiting a persymmetric structure in the received signal. The persymmetric adaptive matched filter (PS-AMF) is used to address this problem, which can significantly alleviate the requirement of secondary data. In this paper, finite-sum expressions for the probability of false alarm of the PS-AMF are derived, which are more convenient to use in calculating the detection threshold. Moreover, the detection probabilities of the PS-AMF are derived. These theoretical results are all confirmed using Monte Carlo simulations.",

keywords = "Adaptive matched filter, Laplace approximation, Persymmetric, adaptive detection",

author = "Jun Liu and Hongbin Li and Braham Himed",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016 ; Conference date: 10-07-2016 Through 13-07-2016",

year = "2016",

month = sep,

day = "15",

doi = "10.1109/SAM.2016.7569617",

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Liu, J, Li, H & Himed, B 2016, Performance analysis of a persymmetric adaptive matched filter. in 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016., 7569617, Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, vol. 2016-September, 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016, Rio de Rio de Janeiro, Brazil, 10/07/16. https://doi.org/10.1109/SAM.2016.7569617

Performance analysis of a persymmetric adaptive matched filter. / Liu, Jun; Li, Hongbin; Himed, Braham.
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016. 2016. 7569617 (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop; Vol. 2016-September).

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

TY - GEN

T1 - Performance analysis of a persymmetric adaptive matched filter

AU - Liu, Jun

AU - Li, Hongbin

AU - Himed, Braham

PY - 2016/9/15

Y1 - 2016/9/15

N2 - We examine the adaptive detection problem in the presence of colored noise with an unknown covariance matrix, by exploiting a persymmetric structure in the received signal. The persymmetric adaptive matched filter (PS-AMF) is used to address this problem, which can significantly alleviate the requirement of secondary data. In this paper, finite-sum expressions for the probability of false alarm of the PS-AMF are derived, which are more convenient to use in calculating the detection threshold. Moreover, the detection probabilities of the PS-AMF are derived. These theoretical results are all confirmed using Monte Carlo simulations.

AB - We examine the adaptive detection problem in the presence of colored noise with an unknown covariance matrix, by exploiting a persymmetric structure in the received signal. The persymmetric adaptive matched filter (PS-AMF) is used to address this problem, which can significantly alleviate the requirement of secondary data. In this paper, finite-sum expressions for the probability of false alarm of the PS-AMF are derived, which are more convenient to use in calculating the detection threshold. Moreover, the detection probabilities of the PS-AMF are derived. These theoretical results are all confirmed using Monte Carlo simulations.

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T3 - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop

BT - 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016

T2 - 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016

Y2 - 10 July 2016 through 13 July 2016

ER -

Performance analysis of a persymmetric adaptive matched filter

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Keywords

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