Digital Underwater Acoustic Communications

Underwater Acoustic Modems
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Day one at ScirocChallenge: social robots and humans meet in a shopping mall. Cubli — A cube that can jump up, balance, and walk across your desk. How do self-driving cars work? Robert J. Peter K. Are you planning to crowdfund your robot startup? Need help spreading the word? The S2C technology can be used to calculate the position of underwater assets.

This feature can be used to position offshore equipment, for navigation of AUVs and ROVs, cartography, diver tracking among other options. The SONOBOT unmanned surface vehicle was developed to provide surveyors, service providers and researchers with a smart lightweight solution for hydrographic surveys and other applications in harbors and inland waters. We design and manufacture wireless underwater communication systems based on bionic concepts, combining state-of-the-art engineering with the best ideas found in nature.

In this section, the main content is divided into two parts, the first part is the algorithm simulation and realization while the second part is the software design and algorithm implementation process. This section introduces the specific process of algorithm implementation while referring to the literature [ 18 ] which is about covert UAC using dolphin sounds.

In the modulation process, the data from the serial port is encoded first and each six bits are converted to decimal digits. The length of the time delay is calculated according to the time delay resolution. Delay difference is modulated between the interval of two signals according to the calculation. After assembling all click signals and time delay together, the synchronization head and the protection interval are added to the header of the signal. The process flow chart of bio-signal modulation is shown in Figure 8.

The frame structure of the complete mimic bio-signal combined with whistle and clicks is shown in Figure 9. Therefore, the time delay can be calculated as:. Here, k is the decimal information transformed by Gray code from a binary information source. For example, if each encoded element has seven bits of information, the encoding time would be divided into parts. As the width and encoding time of each click is variable, the communication data rate of the system can be calculated as:. At the receiver, side synchronization is achieved by the whistle. After synchronization, the protection interval and the first click signal are removed in order to reduce the time of operation as it does not carry any information and the length is known l 0.

The starting position is identified by correlation peaks of the last iteration. Therefore, there is no need to perform correlation for the first click signal and ensure that the length of the signal results in the shortest first operation signal with no loss of information. The correlation peak position minus the length l i is the corresponding time delay. We can obtain the transmitted data after converting the decimal data into binary data. Finally, the system will upload data to the host computer to be displayed through the serial port. The whole process flow chart is shown in Figure The click signals we selected have excellent autocorrelation as shown in Figure Different colors represent the correlation output between different click signals and the click signals group.

Each peak reflects the autocorrelation of the click signals. Table 1 lists the normalized cross correlation and autocorrelation coefficients of each signal. From Table 2 , we can ascertain that the correlation coefficients between the signals are less than 0. We obtained the bit error rate BER curve of the algorithm under white Gaussian noise by simulation. At the same time, we used the real lake channel to test the performance of the algorithm, and used the matching pursuit MP [ 36 ] algorithm to estimate the channel, and then compensate the signal through the virtual time reversal mirror VTRM [ 37 ].

Moreover, in order to verify the performance of the proposed algorithm under the influence of Doppler, we simulated the invariant Doppler factor and various relative motion velocities by resampling, and obtained the bit error rate curve. The results are as shown in Figure Algorithm simulation conditions and results; a Time-varying channel impulse response; b Channel impulse response estimated by the MP method using a dolphin whistle; c Virtual channel after virtual time reversal mirror VTRM by using the estimated channel impulse response; d bit error rate BER of demodulation results.

The underwater channel is derived from Songhua Lake in China. The water depth was about 40 m. The transmitter was about 13 m and the receiving hydrophone was about 12 m below the boats with a distance of m. Furthermore, it can be seen from the simulation results that the Doppler has limited impact on the algorithm when the relative speed between the transmitter and receiver is less than 0.

The software flowchart of this modem is shown in Figure It mainly includes a DSP driver and algorithm realization.

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In addition to the initialization of these modules, a few more steps are needed to complete the algorithm implementation. To realize the algorithm on DSP, we take the whale clicks converted to sixteen bits of vector data.

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The data is stored in the SD card in the modem to realize the modulation and demodulation process in advance. In the initialization process, there are two serial communication processes between the Modem and host computer; the first one is to determine the selection of dolphin calls from the SD card and the second command is to determine the modem working in sending or receiving mode. If it is in receiving mode, we will carry out the FFT process on the frame synchronization signal—it is mainly used in the fast correlation operation to find the synchronization signal and reduce the computing time.

After completing all of the above steps, the system is initialized. After the initialization, the whole system is working in a standby state, awaiting the transmission of serial instructions. If the system receives the sending instructions, it will continue to receive the data from the serial port and begin to carry out the algorithm modulation after receiving the cut-off character instruction.

If the system receives the instructions of data acquisition from the serial port, it begins to collect the signal and carries on the fast correlation operation. After finding the signal by seeking the correlation peak, the system demodulates the signal and the results are sent through the serial port to the host computer. To verify the functionality and performance of the PBC micro-modem, indoor experiments were conducted in a channel pool as shown in Figure The pool length, width and depth are 45 m, 6 m, and 5 m respectively.

For convenience, the transducers are only submerged in the water and the rest of micro-modem is placed on the desk in front of the water pool. The transducer and electronic part of the modem are connected by a cable. Also, each modem is connected to a corresponding computer via a RS interface for control and monitoring.

As the demodulation is mainly carried out by signal correlation, in order to reduce the bit error rate, we take the channel and noise effects into account. We removed the signal from the call library if the correlation coefficient between them is more than 0. To evaluate the similarity between the dolphin-call samples and the received signals through the pool channel, we collected the received signals from the receiver, and the signal and call samples were compared in the spectrogram as follows. A comparison of the spectrogram of the call samples and the received signals is shown in Figure From the spectrum of the received signal, it can be seen that there is multipath superposition on the signal, and there is some noise interference.

After the signal passed through the pool channel, its spectrum changed; however, a certain extent of the spectrogram characteristics of dolphin calls are still maintained. Comparison of the spectrogram of the call sample and the received signals; a The spectrogram of the dolphin calls sample; b The spectrogram of the received signals. The time—frequency analysis and demodulation results are shown in Figure Among them, the two signals were received at different distances 7.

During the two hours of testing, no error occurred and a data rate of The time—frequency analysis and demodulation results; a Transmitted dolphin clicks; b Correlation result of transmitted clicks; c Received clicks at 7. The purpose of this experiment is to verify the algorithm and the performance of the modem. According to the specific needs, we can increase the distance between the clicks and the number of click signals. In this paper, we have designed a portable micro-modem based on the bionic covert UAC algorithm for underwater sensor networks.

Details of Grant

Specifically, it is the first time that a modem has been used to communicate using real dolphin-call signals. It opens the door for secure and covert communication—the message between the divers or UUVs and control center cannot be identified. Additionally, the compact design of the modem has many advantages such as being portable for divers, it can be placed on UUV and it can also be used as a standalone unit for a particular application.

In the pool experiment, we tested the covert UAC algorithm by using the time delay between dolphin sounds and verified that the modem could efficiently perform reliable data transmission over short distances. At a distance of 10 m, a data rate of However, work is still in progress and our current work only uses transducers for lab communication.

We plan to test our modem in the sea or a lake shortly.

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We will try to increase the communication distance as well as the data rate. We will also enhance the circuit of the modem, improve its stability, and reduce its output noise. The existing dolphin sounds library can be expanded, and more algorithms need to be developed to imitate dolphin sounds and realize covert communication. All authors contributed significantly to the work presented in this manuscript. National Center for Biotechnology Information , U. Journal List Sensors Basel v. Sensors Basel. Published online Oct Author information Article notes Copyright and License information Disclaimer.

High-Speed Underwater Acoustic Communications | SpringerLink

Received Aug 11; Accepted Oct This article has been cited by other articles in PMC. Abstract A novel portable underwater acoustic modem is proposed in this paper for covert communication between divers or underwater unmanned vehicles UUVs and divers at a short distance. Keywords: underwater acoustic communication, bionic, underwater acoustic modem, micro-modem, covert, dolphin sounds.

Introduction With the growing demand for marine development, underwater acoustic communication UAC and networks have been used in many fields, such as marine environmental monitoring, natural disaster warning, etc [ 1 , 2 ]. Open in a separate window. Modem Design Our modem is designed specifically for divers to communicate with their partners or UUVs securely as shown in Figure 1. Figure 1. Modem Structure Design The conventional modem structure block diagram is illustrated in Figure 2. Figure 2. Figure 3.


The development of digital underwater acoustic communications is introduced briefly, and then a special emphasis is placed on the essential differences. Digital Underwater Acoustic Communications focuses on describing the differences between underwater acoustic communication channels.

Digital Domain Processing 3. Analog Domain Processing at Transceiver The analog circuit receives the signal from the digital circuit at which point the digital signal is changed into analog signal through AIC Figure 4.