Abstract
For underwater acoustic covert communications, biomimetic covert communications have been developed using dolphin whistles. The conventional biomimetic covert communication methods transmit slightly different signal patterns from real dolphin whistles, which results in a low degree of mimic (DoM). In this paper, we propose a novel biomimetic communication method that preserves the large DoM with a low bit error rate (BER). For the transmission, the proposed method utilizes the various contours of real dolphin whistles with the link information among consecutive whistles, and the proposed receiver uses machine learning based whistle detectors with the aid of the link information. Computer simulations and practical ocean experiments were executed to demonstrate the better BER performance of the proposed method. Ocean experiments demonstrate that the BER of the proposed method was 0.002, while the BER of the conventional Deep Neural Network (DNN) based detector showed 0.36.
Highlights
For military underwater acoustic (UWA) communication systems, low probabilities of detection/intercept (LPD/LPI) are important parameters [1,2,3,4,5,6,7]
We propose a biomimetic covert communication scheme that modulates the information bits into various whistle patterns to increase the degree of mimic (DoM) with the link information among consecutive transmitted whistles, and detects the distorted whistles—via the link information—with the UWA channel using a machine learning based detector
We propose a biomimetic communication scheme: the transmitter modulates the whistles with the larger distances and DoM based on the link information among adjacent whistles, and the receiver demodulates and detects the distorted whistles using a directional acyclic graph (DAG)-net based long-short term memory (LSTM) with additional link information among whistles
Summary
For military underwater acoustic (UWA) communication systems, low probabilities of detection/intercept (LPD/LPI) are important parameters [1,2,3,4,5,6,7]. In [9], the phase shift keying (PSK) modulation with dolphin whistles was utilized, but BER at an Signal to Noise Ratio (SNR) range of 5 dB to 10 dB showed 10−2 , which was inappropriate for communication, and the scheme was not tested in ocean experiments. Even though the methods in [14,15] were developed to utilize dolphin whistles without distorting the whistles, the algorithm in [14] showed a relatively large BER performance (10−2 ) at an SNR range of 5 dB to 10 dB, and the scheme in [15] had to utilize only high auto-correlated whistles for modulation, which decreased the covertness. We propose a biomimetic covert communication scheme that modulates the information bits into various whistle patterns to increase the DoM with the link information among consecutive transmitted whistles, and detects the distorted whistles—via the link information—with the UWA channel using a machine learning based detector.
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