Distributed Fuzzy CFAR Detection for Weibull Clutter

Amir ZAIMBASHI; Mohammad Reza TABAN; Mohammad Mehdi NAYEBI

doi:10.1093/ietcom/e91-b.2.543

Distributed Fuzzy CFAR Detection for Weibull Clutter

Amir ZAIMBASHI, Mohammad Reza TABAN, Mohammad Mehdi NAYEBI

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In Distributed detection systems, restricting the output of the local decision to one bit certainly implies a substantial information loss. In this paper, we consider the fuzzy detection, which uses a function called membership function for mapping the observation space of each local detector to a value between 0 and 1, indicating the degree of assurance about presence or absence of a signal. In this case, we examine the problem of distributed Maximum Likelihood (ML) and Order Statistic (OS) constant false alarm rate (CFAR) detections using fuzzy fusion rules such as "Algebraic Product"(AP), "Algebraic Sum"(AS), "Union"(Un) and "Intersection"(IS) in the fusion centre. For the Weibull clutter, the expression of the membership function based on the ML or OS CFAR processors in the local detectors is also obtained. For comparison, we consider a binary distributed detector, which uses the Maximum Likelihood and Algebraic Product (MLAP) or Order Statistic and Algebraic Product (OSAP) CFAR processors as the local detectors. In homogenous and non homogenous situations, multiple targets or clutter edge, the performances of the fuzzy and binary distributed detectors are analyzed and compared. The simulation results indicate the superior and robust performance of the distributed systems using fuzzy detection in the homogenous and non homogenous situations.

Publication: IEICE TRANSACTIONS on Communications Vol.E91-B No.2 pp.543-552

Publication Date: 2008/02/01

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Online ISSN: 1745-1345

DOI: 10.1093/ietcom/e91-b.2.543

Type of Manuscript: PAPER

Category: Sensing

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Amir ZAIMBASHI, Mohammad Reza TABAN, Mohammad Mehdi NAYEBI, "Distributed Fuzzy CFAR Detection for Weibull Clutter" in IEICE TRANSACTIONS on Communications, vol. E91-B, no. 2, pp. 543-552, February 2008, doi: 10.1093/ietcom/e91-b.2.543.
Abstract: In Distributed detection systems, restricting the output of the local decision to one bit certainly implies a substantial information loss. In this paper, we consider the fuzzy detection, which uses a function called membership function for mapping the observation space of each local detector to a value between 0 and 1, indicating the degree of assurance about presence or absence of a signal. In this case, we examine the problem of distributed Maximum Likelihood (ML) and Order Statistic (OS) constant false alarm rate (CFAR) detections using fuzzy fusion rules such as "Algebraic Product"(AP), "Algebraic Sum"(AS), "Union"(Un) and "Intersection"(IS) in the fusion centre. For the Weibull clutter, the expression of the membership function based on the ML or OS CFAR processors in the local detectors is also obtained. For comparison, we consider a binary distributed detector, which uses the Maximum Likelihood and Algebraic Product (MLAP) or Order Statistic and Algebraic Product (OSAP) CFAR processors as the local detectors. In homogenous and non homogenous situations, multiple targets or clutter edge, the performances of the fuzzy and binary distributed detectors are analyzed and compared. The simulation results indicate the superior and robust performance of the distributed systems using fuzzy detection in the homogenous and non homogenous situations.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e91-b.2.543/_p

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@ARTICLE{e91-b_2_543,
author={Amir ZAIMBASHI, Mohammad Reza TABAN, Mohammad Mehdi NAYEBI, },
journal={IEICE TRANSACTIONS on Communications},
title={Distributed Fuzzy CFAR Detection for Weibull Clutter},
year={2008},
volume={E91-B},
number={2},
pages={543-552},
abstract={In Distributed detection systems, restricting the output of the local decision to one bit certainly implies a substantial information loss. In this paper, we consider the fuzzy detection, which uses a function called membership function for mapping the observation space of each local detector to a value between 0 and 1, indicating the degree of assurance about presence or absence of a signal. In this case, we examine the problem of distributed Maximum Likelihood (ML) and Order Statistic (OS) constant false alarm rate (CFAR) detections using fuzzy fusion rules such as "Algebraic Product"(AP), "Algebraic Sum"(AS), "Union"(Un) and "Intersection"(IS) in the fusion centre. For the Weibull clutter, the expression of the membership function based on the ML or OS CFAR processors in the local detectors is also obtained. For comparison, we consider a binary distributed detector, which uses the Maximum Likelihood and Algebraic Product (MLAP) or Order Statistic and Algebraic Product (OSAP) CFAR processors as the local detectors. In homogenous and non homogenous situations, multiple targets or clutter edge, the performances of the fuzzy and binary distributed detectors are analyzed and compared. The simulation results indicate the superior and robust performance of the distributed systems using fuzzy detection in the homogenous and non homogenous situations.},
keywords={},
doi={10.1093/ietcom/e91-b.2.543},
ISSN={1745-1345},
month={February},}

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TY - JOUR
TI - Distributed Fuzzy CFAR Detection for Weibull Clutter
T2 - IEICE TRANSACTIONS on Communications
SP - 543
EP - 552
AU - Amir ZAIMBASHI
AU - Mohammad Reza TABAN
AU - Mohammad Mehdi NAYEBI
PY - 2008
DO - 10.1093/ietcom/e91-b.2.543
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E91-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2008
AB - In Distributed detection systems, restricting the output of the local decision to one bit certainly implies a substantial information loss. In this paper, we consider the fuzzy detection, which uses a function called membership function for mapping the observation space of each local detector to a value between 0 and 1, indicating the degree of assurance about presence or absence of a signal. In this case, we examine the problem of distributed Maximum Likelihood (ML) and Order Statistic (OS) constant false alarm rate (CFAR) detections using fuzzy fusion rules such as "Algebraic Product"(AP), "Algebraic Sum"(AS), "Union"(Un) and "Intersection"(IS) in the fusion centre. For the Weibull clutter, the expression of the membership function based on the ML or OS CFAR processors in the local detectors is also obtained. For comparison, we consider a binary distributed detector, which uses the Maximum Likelihood and Algebraic Product (MLAP) or Order Statistic and Algebraic Product (OSAP) CFAR processors as the local detectors. In homogenous and non homogenous situations, multiple targets or clutter edge, the performances of the fuzzy and binary distributed detectors are analyzed and compared. The simulation results indicate the superior and robust performance of the distributed systems using fuzzy detection in the homogenous and non homogenous situations.
ER -