Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold Method
This paper proposes a joint time–frequency analysis method that combines <i>Rao</i> detector with dynamic sliding thresholds to enhance the detection performance of electric source axial frequency magnetic field signals. For each signal-to-noise ratio (SNR) point, 1000 Monte Carlo simula...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/11/3364 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849330828906070016 |
|---|---|
| author | Yi Li Jiawei Zhang |
| author_facet | Yi Li Jiawei Zhang |
| author_sort | Yi Li |
| collection | DOAJ |
| description | This paper proposes a joint time–frequency analysis method that combines <i>Rao</i> detector with dynamic sliding thresholds to enhance the detection performance of electric source axial frequency magnetic field signals. For each signal-to-noise ratio (SNR) point, 1000 Monte Carlo simulations were independently conducted, with SNR ranging from 15 dB to −30 dB. The results show that the proposed method maintains high detection rates even at extremely low SNRs, achieving about 90% detection probability at −13 dB, significantly outperforming traditional energy detectors (with a threshold of 2 dB). Under conditions where the detection probability is ≥90% and the false alarm probability is 10<sup>−3</sup>, the SNR threshold for the <i>Rao</i> detector is reduced by 15 dB compared to energy detectors, greatly improving detection performance. Even at lower SNRs (−30 dB), the <i>Rao</i> detector still maintains a certain detection rate, while the detection rate of energy detectors rapidly drops to zero. Further analysis of the impact of different frequencies (1–5 Hz) and CPA distances (45–80 cm) on performance verifies the algorithm’s robustness and practicality in complex non-Gaussian noise environments. This method provides an effective technical solution for low SNR detection of ship axial frequency magnetic fields and has good potential for practical application. |
| format | Article |
| id | doaj-art-567b2c947d2d48b5b29b6770e1858f8b |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-567b2c947d2d48b5b29b6770e1858f8b2025-08-20T03:46:49ZengMDPI AGSensors1424-82202025-05-012511336410.3390/s25113364Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold MethodYi Li0Jiawei Zhang1Naval University of Engineering, Wuhan 430030, ChinaNaval University of Engineering, Wuhan 430030, ChinaThis paper proposes a joint time–frequency analysis method that combines <i>Rao</i> detector with dynamic sliding thresholds to enhance the detection performance of electric source axial frequency magnetic field signals. For each signal-to-noise ratio (SNR) point, 1000 Monte Carlo simulations were independently conducted, with SNR ranging from 15 dB to −30 dB. The results show that the proposed method maintains high detection rates even at extremely low SNRs, achieving about 90% detection probability at −13 dB, significantly outperforming traditional energy detectors (with a threshold of 2 dB). Under conditions where the detection probability is ≥90% and the false alarm probability is 10<sup>−3</sup>, the SNR threshold for the <i>Rao</i> detector is reduced by 15 dB compared to energy detectors, greatly improving detection performance. Even at lower SNRs (−30 dB), the <i>Rao</i> detector still maintains a certain detection rate, while the detection rate of energy detectors rapidly drops to zero. Further analysis of the impact of different frequencies (1–5 Hz) and CPA distances (45–80 cm) on performance verifies the algorithm’s robustness and practicality in complex non-Gaussian noise environments. This method provides an effective technical solution for low SNR detection of ship axial frequency magnetic fields and has good potential for practical application.https://www.mdpi.com/1424-8220/25/11/3364shipaxial frequency magnetic field<i>Rao</i> detectornon-Gaussian noisesliding threshold |
| spellingShingle | Yi Li Jiawei Zhang Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold Method Sensors ship axial frequency magnetic field <i>Rao</i> detector non-Gaussian noise sliding threshold |
| title | Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold Method |
| title_full | Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold Method |
| title_fullStr | Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold Method |
| title_full_unstemmed | Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold Method |
| title_short | Underwater Low-Frequency Magnetic Field Detection Based on <i>Rao</i>’s Sliding Threshold Method |
| title_sort | underwater low frequency magnetic field detection based on i rao i s sliding threshold method |
| topic | ship axial frequency magnetic field <i>Rao</i> detector non-Gaussian noise sliding threshold |
| url | https://www.mdpi.com/1424-8220/25/11/3364 |
| work_keys_str_mv | AT yili underwaterlowfrequencymagneticfielddetectionbasedoniraoisslidingthresholdmethod AT jiaweizhang underwaterlowfrequencymagneticfielddetectionbasedoniraoisslidingthresholdmethod |