Extremely Weak Signal Detection Algorithm of Multi-Pixel Photon Detector
For the detection of extremely weak signals in underwater long distance wireless optical communication, the Geiger mode of the multi pixel photon detector has serious pulse superposition effect and Poisson noise, which leads to counting difficulties and affects the measurement accuracy. This paper p...
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| Vydané v: | Journal of physics. Conference series Ročník 2476; číslo 1; s. 12026 - 12030 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Bristol
IOP Publishing
01.04.2023
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| ISSN: | 1742-6588, 1742-6596 |
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| Abstract | For the detection of extremely weak signals in underwater long distance wireless optical communication, the Geiger mode of the multi pixel photon detector has serious pulse superposition effect and Poisson noise, which leads to counting difficulties and affects the measurement accuracy. This paper proposes a deconvolution joint generalized Anscombe transform (DUGAT) detection algorithm. First, the deconvolution filtering technology is used to process the weak signal to reduce the superposition effect and converge the pulse width. Secondly, the noise signal of Poisson+Gaussian (P+G) distribution is converted into Gaussian variable by using generalized Anscombe transform (GAT), which is equivalent to additive Gaussian noise signal. Finally, the symbols are counted by hard decision algorithm. The experimental results show that the sensitivity of this algorithm is improved by 8.57dB and 9.95dB respectively compared with the traditional AR and ML detection algorithms. |
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| AbstractList | For the detection of extremely weak signals in underwater long distance wireless optical communication, the Geiger mode of the multi pixel photon detector has serious pulse superposition effect and Poisson noise, which leads to counting difficulties and affects the measurement accuracy. This paper proposes a deconvolution joint generalized Anscombe transform (DUGAT) detection algorithm. First, the deconvolution filtering technology is used to process the weak signal to reduce the superposition effect and converge the pulse width. Secondly, the noise signal of Poisson+Gaussian (P+G) distribution is converted into Gaussian variable by using generalized Anscombe transform (GAT), which is equivalent to additive Gaussian noise signal. Finally, the symbols are counted by hard decision algorithm. The experimental results show that the sensitivity of this algorithm is improved by 8.57dB and 9.95dB respectively compared with the traditional AR and ML detection algorithms. |
| Author | yang, Y Zhao, PR zhang, JL Min, ZW Wang, XB Yang, FM |
| Author_xml | – sequence: 1 givenname: Y surname: yang fullname: yang, Y organization: School of Electronic Engineering, Xi’an University of Posts and Telecommunications , China – sequence: 2 givenname: PR surname: Zhao fullname: Zhao, PR organization: School of Electronic Engineering, Xi’an University of Posts and Telecommunications , China – sequence: 3 givenname: XB surname: Wang fullname: Wang, XB organization: Key Laboratory of Underwater Information and Control, China Shipbuilding Industry Corporation 705 Research Institute , China – sequence: 4 givenname: JL surname: zhang fullname: zhang, JL organization: School of Electronic Engineering, Xi’an University of Posts and Telecommunications , China – sequence: 5 givenname: FM surname: Yang fullname: Yang, FM organization: School of Electronic Engineering, Xi’an University of Posts and Telecommunications , China – sequence: 6 givenname: ZW surname: Min fullname: Min, ZW organization: School of Electronic Engineering, Xi’an University of Posts and Telecommunications , China |
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| Cites_doi | 10.1109/JPHOT.2016.2633560 10.3788/OPE.20111905.0972 10.1016/j.optcom.2019.01.031 10.1016/j.optcom.2018.04.008 10.1109/TAES.1978.308688 10.1364/OE.25.022178 10.1364/OE.410026 10.1364/AO.58.009808 10.1109/LPT.2015.2402151 |
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| SubjectTerms | Algorithms Deconvolution Deconvolution FilteringTechnique Extremely Weak Signal Detection Generalized Anscombe Transform Normal distribution Optical communication Optical Wireless Communication Photons Physics Pixels Pulse duration Random noise Signal detection System Performance Wireless communications |
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| Title | Extremely Weak Signal Detection Algorithm of Multi-Pixel Photon Detector |
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