Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization Algorithm
The wideband underwater acoustic multipath channel can be modeled as a multi-scale multi-lag (MSML) channel because signals from different paths might experience different Doppler scales. This brings great challenge to channel parameter estimation. In this paper, we propose a novel algorithm for par...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/7875409/ |
| _version_ | 1818644499738394624 |
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| author | Xing Zhang Kang Song Chunguo Li Luxi Yang |
| author_facet | Xing Zhang Kang Song Chunguo Li Luxi Yang |
| author_sort | Xing Zhang |
| collection | DOAJ |
| description | The wideband underwater acoustic multipath channel can be modeled as a multi-scale multi-lag (MSML) channel because signals from different paths might experience different Doppler scales. This brings great challenge to channel parameter estimation. In this paper, we propose a novel algorithm for parameter estimation of MSML channels. This new algorithm is a modified particle swarm optimization (MPSO) algorithm, which can estimate the parameters of the Doppler scale, the time delay, and the amplitude simultaneously for each individual path. Comparing to PSO algorithm, MPSO algorithm uses a multipath list to record positions and fitness values of particles whose fitness values are selected as lbests, and uses these lbests to update particles' velocities at each iteration. As for training sequence, we employ the zero correlation zone sequence which has excellent correlation properties. Computer simulation is used to evaluate the proposed algorithm in comparison with the matching pursuit (MP)-based method and the fractional Fourier transform (FrFT)-based method. Simulation results confirm that the proposed MPSO algorithm outperforms both MP-based method and FrFT-based method in estimation accuracy as well as computation complexity. |
| first_indexed | 2024-12-17T00:15:50Z |
| format | Article |
| id | doaj.art-8eab332d558c461f92a17fbd92b8b1bd |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T00:15:50Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8eab332d558c461f92a17fbd92b8b1bd2022-12-21T22:10:42ZengIEEEIEEE Access2169-35362017-01-0154808482010.1109/ACCESS.2017.26811017875409Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization AlgorithmXing Zhang0https://orcid.org/0000-0002-5972-8325Kang Song1Chunguo Li2Luxi Yang3Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, Southeast University, Nanjing, ChinaKey Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, Southeast University, Nanjing, ChinaKey Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, Southeast University, Nanjing, ChinaKey Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, Southeast University, Nanjing, ChinaThe wideband underwater acoustic multipath channel can be modeled as a multi-scale multi-lag (MSML) channel because signals from different paths might experience different Doppler scales. This brings great challenge to channel parameter estimation. In this paper, we propose a novel algorithm for parameter estimation of MSML channels. This new algorithm is a modified particle swarm optimization (MPSO) algorithm, which can estimate the parameters of the Doppler scale, the time delay, and the amplitude simultaneously for each individual path. Comparing to PSO algorithm, MPSO algorithm uses a multipath list to record positions and fitness values of particles whose fitness values are selected as lbests, and uses these lbests to update particles' velocities at each iteration. As for training sequence, we employ the zero correlation zone sequence which has excellent correlation properties. Computer simulation is used to evaluate the proposed algorithm in comparison with the matching pursuit (MP)-based method and the fractional Fourier transform (FrFT)-based method. Simulation results confirm that the proposed MPSO algorithm outperforms both MP-based method and FrFT-based method in estimation accuracy as well as computation complexity.https://ieeexplore.ieee.org/document/7875409/Multi-scale multi-lag (MSML) channelparameter estimationmodified particle swarm optimization (MPSO) algorithmzero correlation zone (ZCZ) sequence |
| spellingShingle | Xing Zhang Kang Song Chunguo Li Luxi Yang Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization Algorithm IEEE Access Multi-scale multi-lag (MSML) channel parameter estimation modified particle swarm optimization (MPSO) algorithm zero correlation zone (ZCZ) sequence |
| title | Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization Algorithm |
| title_full | Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization Algorithm |
| title_fullStr | Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization Algorithm |
| title_full_unstemmed | Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization Algorithm |
| title_short | Parameter Estimation for Multi-Scale Multi-Lag Underwater Acoustic Channels Based on Modified Particle Swarm Optimization Algorithm |
| title_sort | parameter estimation for multi scale multi lag underwater acoustic channels based on modified particle swarm optimization algorithm |
| topic | Multi-scale multi-lag (MSML) channel parameter estimation modified particle swarm optimization (MPSO) algorithm zero correlation zone (ZCZ) sequence |
| url | https://ieeexplore.ieee.org/document/7875409/ |
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