Fresnel Domain Sector Modulation LFM Signal for Underwater Integrated Communication and Detection

The Internet of Underwater Things (IoUT) technology has been gaining importance in smart ocean investigation in recent years. The integrated system for underwater detection and communication (ISUDC) is considered a crucial technique for IoUT due to its potential to decrease equipment size and power consumption. The linear frequency modulation (LFM) signal has the characteristics of large time-bandwidth product and has great advantages in detection. However, it has high complexity and low robustness of communication in ISUDC. To address this issue, this article proposes a sector-modulated LFM (SM-LFM) signal for ISUDC. In terms of communication, it divides Fresnel domain into equal length sectors. Then, data is loaded by activating different sector. At the communication receiver, by establishing a relationship between the Dirac function in the Fresnel domain and the channel impulse response (CIR) in the time domain, data is demodulated by finding CIR’s main path without channel estimation or equalization. In terms of detection, SM-LFM has an improvement in the maximum unambiguous velocity by calculating relative radial velocity in the Fresnel domain instead of the frequency domain. Numerical simulations and lake experiments have confirmed that the SM-LFM signal can deliver superior robustness and easy-to-use advantages for underwater active detection and communication.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-10-10
DOI
https://doi.org/10.1109/jiot.2024.3477576
Citations
3
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
1.01

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article

Fresnel Domain Sector Modulation LFM Signal for Underwater Integrated Communication and Detection

Xiaomei Fu, Guangyao Han, Quan Tao, Junlong Wang et al.
3 citations
IEEE Internet of Things Journal
Underwater Vehicles and Communication Systems
1.01
article

Fresnel Domain Sector Modulation LFM Signal for Underwater Integrated Communication and Detection

Xiaomei Fu, Guangyao Han, Quan Tao, Junlong Wang, Jixin Bao
article en
3 citations

Abstract

The Internet of Underwater Things (IoUT) technology has been gaining importance in smart ocean investigation in recent years. The integrated system for underwater detection and communication (ISUDC) is considered a crucial technique for IoUT due to its potential to decrease equipment size and power consumption. The linear frequency modulation (LFM) signal has the characteristics of large time-bandwidth product and has great advantages in detection. However, it has high complexity and low robustness of communication in ISUDC. To address this issue, this article proposes a sector-modulated LFM (SM-LFM) signal for ISUDC. In terms of communication, it divides Fresnel domain into equal length sectors. Then, data is loaded by activating different sector. At the communication receiver, by establishing a relationship between the Dirac function in the Fresnel domain and the channel impulse response (CIR) in the time domain, data is demodulated by finding CIR’s main path without channel estimation or equalization. In terms of detection, SM-LFM has an improvement in the maximum unambiguous velocity by calculating relative radial velocity in the Fresnel domain instead of the frequency domain. Numerical simulations and lake experiments have confirmed that the SM-LFM signal can deliver superior robustness and easy-to-use advantages for underwater active detection and communication.

IEEE Internet of Things JournalVol. 12(3)
Tianjin University of Science and Technology (CN), Northwestern Polytechnical University (CN), Ministry of Natural Resources (CN), Northwest University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 25%
Underwater Vehicles and Communication Systems
1.01
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Fresnel Domain Sector Modulation LFM Signal for Underwater Integrated Communication and Detection — Xiaomei Fu, Guangyao Han, et al. · IEEE Internet of Things Journal (2024) | TGRS Research Map | TGRS