Locally optimal detector design in impulsive noise with unknown distribution
Abstract This paper designs the locally optimal detector (LOD) in additive white impulsive noise with unknown distribution. Unlike traditional LODs derived from a known or approximated noise probability density function (PDF), the LOD proposed in this paper is achieved by designing the zero-memory n...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2018-06-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13634-018-0560-x |
| _version_ | 1811197395488210944 |
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| author | Zhongtao Luo Peng Lu Gang Zhang |
| author_facet | Zhongtao Luo Peng Lu Gang Zhang |
| author_sort | Zhongtao Luo |
| collection | DOAJ |
| description | Abstract This paper designs the locally optimal detector (LOD) in additive white impulsive noise with unknown distribution. Unlike traditional LODs derived from a known or approximated noise probability density function (PDF), the LOD proposed in this paper is achieved by designing the zero-memory non-linearity (ZMNL) function based on real data. After the PDF estimation in a nonparametric way by a kernel method, the ZMNL function is designed as a piecewise differentiable function consisting of a polynomial function and inverse proportional functions. Then, we analyze the detection performance and develop the constant false alarm ratio technique. Simulation results show that the LOD design is near-optimal in α-stable noise and the optimal in real atmospheric data, compared with the maximum likelihood detector of α-stable distribution. |
| first_indexed | 2024-04-12T01:14:00Z |
| format | Article |
| id | doaj.art-19b7f7032c5948288d4980328f166c9d |
| institution | Directory Open Access Journal |
| issn | 1687-6180 |
| language | English |
| last_indexed | 2024-04-12T01:14:00Z |
| publishDate | 2018-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-19b7f7032c5948288d4980328f166c9d2022-12-22T03:54:01ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802018-06-012018111010.1186/s13634-018-0560-xLocally optimal detector design in impulsive noise with unknown distributionZhongtao Luo0Peng Lu1Gang Zhang2School of Communication and Information Engineering, Chongqing University of Posts and TelecommunicationsSchool of Communication and Information Engineering, Chongqing University of Posts and TelecommunicationsSchool of Communication and Information Engineering, Chongqing University of Posts and TelecommunicationsAbstract This paper designs the locally optimal detector (LOD) in additive white impulsive noise with unknown distribution. Unlike traditional LODs derived from a known or approximated noise probability density function (PDF), the LOD proposed in this paper is achieved by designing the zero-memory non-linearity (ZMNL) function based on real data. After the PDF estimation in a nonparametric way by a kernel method, the ZMNL function is designed as a piecewise differentiable function consisting of a polynomial function and inverse proportional functions. Then, we analyze the detection performance and develop the constant false alarm ratio technique. Simulation results show that the LOD design is near-optimal in α-stable noise and the optimal in real atmospheric data, compared with the maximum likelihood detector of α-stable distribution.http://link.springer.com/article/10.1186/s13634-018-0560-xLocally optimal detectorZMNL functionNon-Gaussian distributionPolynomial fitting |
| spellingShingle | Zhongtao Luo Peng Lu Gang Zhang Locally optimal detector design in impulsive noise with unknown distribution EURASIP Journal on Advances in Signal Processing Locally optimal detector ZMNL function Non-Gaussian distribution Polynomial fitting |
| title | Locally optimal detector design in impulsive noise with unknown distribution |
| title_full | Locally optimal detector design in impulsive noise with unknown distribution |
| title_fullStr | Locally optimal detector design in impulsive noise with unknown distribution |
| title_full_unstemmed | Locally optimal detector design in impulsive noise with unknown distribution |
| title_short | Locally optimal detector design in impulsive noise with unknown distribution |
| title_sort | locally optimal detector design in impulsive noise with unknown distribution |
| topic | Locally optimal detector ZMNL function Non-Gaussian distribution Polynomial fitting |
| url | http://link.springer.com/article/10.1186/s13634-018-0560-x |
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