A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals
Reliable and efficient sensing and tracking of multiple weak or time-varying frequency line components in underwater acoustic signals is the topic of this paper. We propose a method for automatic detection and tracking of multiple frequency lines in lofargram based on hidden Markov model (HMM). Inst...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/22/4866 |
| _version_ | 1828117912998641664 |
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| author | Xinwei Luo Zihan Shen |
| author_facet | Xinwei Luo Zihan Shen |
| author_sort | Xinwei Luo |
| collection | DOAJ |
| description | Reliable and efficient sensing and tracking of multiple weak or time-varying frequency line components in underwater acoustic signals is the topic of this paper. We propose a method for automatic detection and tracking of multiple frequency lines in lofargram based on hidden Markov model (HMM). Instead of being directly subjected to frequency line tracking, the whole lofargram is first segmented into several sub-lofargrams. Then, the sub-lofargrams suspected to contain frequency lines are screened. In these sub-lofargrams, the HMM-based method is used for detection of multiple frequency lines. Using image stitching and statistical model method, the frequency lines with overlapping parts detected by different sub-lofargrams are merged to obtain the final detection results. The method can effectively detect multiple time-varying frequency lines of underwater acoustic signals while ensuring the performance under the condition of low signal-to-noise ratio (SNR). It can be concluded that the proposed algorithm can provide better multiple frequency lines sensing ability while greatly reducing the amount of calculations and providing potential techniques for feature sensing and tracking processing of unattended equipment such as sonar buoys and submerged buoys. |
| first_indexed | 2024-04-11T13:23:12Z |
| format | Article |
| id | doaj.art-2299d23ce59146cd982c4a7ec73897d3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T13:23:12Z |
| publishDate | 2019-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2299d23ce59146cd982c4a7ec73897d32022-12-22T04:22:09ZengMDPI AGSensors1424-82202019-11-011922486610.3390/s19224866s19224866A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic SignalsXinwei Luo0Zihan Shen1Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, Southeast University, Nanjing 210096, ChinaKey Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, Southeast University, Nanjing 210096, ChinaReliable and efficient sensing and tracking of multiple weak or time-varying frequency line components in underwater acoustic signals is the topic of this paper. We propose a method for automatic detection and tracking of multiple frequency lines in lofargram based on hidden Markov model (HMM). Instead of being directly subjected to frequency line tracking, the whole lofargram is first segmented into several sub-lofargrams. Then, the sub-lofargrams suspected to contain frequency lines are screened. In these sub-lofargrams, the HMM-based method is used for detection of multiple frequency lines. Using image stitching and statistical model method, the frequency lines with overlapping parts detected by different sub-lofargrams are merged to obtain the final detection results. The method can effectively detect multiple time-varying frequency lines of underwater acoustic signals while ensuring the performance under the condition of low signal-to-noise ratio (SNR). It can be concluded that the proposed algorithm can provide better multiple frequency lines sensing ability while greatly reducing the amount of calculations and providing potential techniques for feature sensing and tracking processing of unattended equipment such as sonar buoys and submerged buoys.https://www.mdpi.com/1424-8220/19/22/4866frequency line detectionlofargramhmmlofargram segmentation |
| spellingShingle | Xinwei Luo Zihan Shen A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals Sensors frequency line detection lofargram hmm lofargram segmentation |
| title | A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals |
| title_full | A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals |
| title_fullStr | A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals |
| title_full_unstemmed | A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals |
| title_short | A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals |
| title_sort | sensing and tracking algorithm for multiple frequency line components in underwater acoustic signals |
| topic | frequency line detection lofargram hmm lofargram segmentation |
| url | https://www.mdpi.com/1424-8220/19/22/4866 |
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