This paper shows experimental analysis of an underwater robot localization method based on particle filter(PF). The method uses time difference of arrival(TDOA) of acoustic signals from beacons around a robot. Simulation results reveal dependency of the performance of the method upon degree of uncertainty of sensor data and robot motion. Also comparison of the PF method with the least squares method of spherical interpolation and spherical intersection is provided. Since the PF method uses both the internal motion information as well as TDOA, its estimation is more accurate and robust to the sensor and motion uncertainty than the least squares methods.
This paper proposes a novel method for acoustically and wirelessly transmitting data underwater with a high transmission rate. The method uses the most promising physical layer and multiple access technique (i.e., the code division multiple channel access technique) to divide the channel into subchannels. Data is transmitted through these subchannels. The codes are pseudo-random noise (PN) sequences. In the spread-spectrum technique, a signal such as electrical, electromagnetic, acoustic signal generated in a particular bandwidth is deliberately spread in the frequency domain, which results in a signal with a wider bandwidth. This paper reviews the possibility of application of the direct-sequence code division multiple access (DS-CDMA) technique in an underwater system using MATLAB. As the result of our review, we recognize that the DS-CDMA technique can be applied to underwater environments.
It is very difficult to design an underwater communication system because of multipath, Doppler effects, noise, and attenuation. These factors lead to errors in the communication performance and maximum propagation distance. In this study, we calculate the distance that can be realized using the direct-sequence code division multiple access (DS-CDMA) technique with direct-sequence spread spectrum (DSSS) in an underwater communication system considering only the attenuation and noise. We also compare the estimated and calculated propagation distances obtained for several different scenarios.
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