scholarly journals Design and Evaluation of an Acoustic Modem for a Small Autonomous Unmanned Vehicle

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2923 ◽  
Author(s):  
Zheng ◽  
Tong ◽  
Li ◽  
Tao ◽  
Song ◽  
...  
Keyword(s):  
Spread Spectrum ◽  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Sampling Rate ◽  
Low Complexity ◽  
Direct Sequence Spread Spectrum ◽  
Analog To Digital ◽  
System Overhead ◽  
Compensation Approach ◽  
Acoustic Modem

Design of underwater acoustic (UWA) modems for compact-sized, underwater platforms such as autonomous underwater vehicles (AUVs) is challenging because of the practical requirement to keep an engineering balance between the performance and the system overhead. Considering this type of mobile communication scenario, Doppler spread as well as the multipath draws substantial attention in implementing the system’s design and engineering. Specifically, for a small AUV, the large computational complexity of real-time resampling for the classic Doppler correction poses significant difficulty for the limited capability of the low-cost processor. In this paper, by adopting an adjustable AD (analog-to-digital) sampling rate, a Doppler compensation approach is proposed to enable low-complexity hardware implementation. Based on this, a direct sequence spread spectrum (DSSS) acoustic modem is designed for a low-cost, small-sized AUV. Meanwhile, the performance evaluation of this acoustic modem is conducted in terms of the robustness upon varying Doppler as well as AUV integration. Finally, experimental results performed on a commercial, small-sized AUV under different speeds are reported to verify the effectiveness of the proposed acoustic modem.

Downsampling Direct Sequence Spread Spectrum Signal Using Orthogonal Pretreatment

2014 ◽  
Vol 610 ◽  
pp. 944-948
Author(s):  
Jin Bo Zhang ◽  
Jian Cheng ◽  
Lei Yang
Keyword(s):  
Spread Spectrum ◽  
Strong Correlation ◽  
Sampling Rate ◽  
Direct Sequence Spread Spectrum ◽  
Direct Sequence ◽  
Sensing Matrix ◽  
Pretreatment Method ◽  
Reconstructed Signal ◽  
Nyquist Rate ◽  
Simulation Results

The Direct Sequence Spread Spectrum (DSSS) signal is widely used because of its good concealment and anti-jamming performance. The Compressive Sensing (CS) theory reduced the sampling rate of the DSSS signal effectively compared with the traditional Nyquist-rate sampling theory. While in the process of CS sampling the sensing matrix and the sparse basis generally have a strong correlation when the DSSS signal is decomposed with a complete dictionary. This paper presents a novel orthogonal pretreatment method with which the incoherence between sensing matrix and sparse basis can be improved. As a result, the reconstructed signal is more accurate. Simulation results demonstrate that this method is effective and efficient.

Review of analog-to-information converters

2019 ◽  
pp. 6-12
Author(s):  
M. N. Polunin ◽  
A. V. Bykova
Keyword(s):  
Spread Spectrum ◽  
Traditional Approach ◽  
Sampling Rate ◽  
Analog To Digital ◽  
Compressed Sampling ◽  
Alternative Approach ◽  
Processing Information ◽  
Random Demodulator ◽  
High Power Consumption ◽  
Modulated Wideband Converter

The implementation of high‑throughput systems with the traditional approach to the discretization of the analog signal according to the Kotelnikov theorem is faced with the problems of high power consumption and the need to store and transfer large amounts of data. An alternative approach to sampling and processing information is based on advances in the compressed sampling theory. The paper provides a brief overview of the main provisions of this theory and considers examples of its use in practice for the implementation of information reading systems – analog‑to‑information converters. The purpose of these devices is to reduce the pressure on conventional analog‑to‑digital converters, to reduce the sampling rate and the amount of output data. The main architectures of analog‑information converters are considered: non‑uniform sampling, random filter, random demodulator, modulated wideband converter, compressive multiplexer, random modulator pre‑integrator, spread spectrum random modulator pre‑integrator.

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