Study On Adaptive-resolution Data Recovery In Three-dimension Underwater Acoustic Network

Oceans are significant sources to maintain the existence of mankind and promote social progress. Wireless Sensor Networks(WSNs) have been becoming significant facilities helping people to cognize the oceans and exploit marine resources owing to their flexible deployment, low cost and extensive coverage. Due to rapid attenuation of electromagnetic wave in water, underwater sensor networks mostly communicate via acoustic wave. Furthermore, severe underwater environment, along with sensor nodes’ communication and energy consumption problem greatly restrict the application of Underwater Acoustic Sensor Networks(UASNs). Compressed Sensing(CS) theory asserts that signals can be recovered from far fewer samples than traditional methods use, if the signal is sparse in a proper basis, thus gets widely attention since proposed. Applying CS theory in UASNs significantly reduces the data collection quantity, and relieves the pressure of power consumption and bandwidth requirement in data transmission, thus prolongs the network lifetime. This thesis mainly study the data collection system in three-dimensions underwater acoustic sensor networks based on CS theory. The adaptive resolution data reconstruction and energy-efficient routing scheme are emphases of this thesis. Ultimately, the compromise between network lifetime and data quality is achieved.Firstly, a data recovery scheme with adaptive resolution based on compressed sensing theory is raised. To resolve the problem of data recovery error increase, caused by insufficient received packets due to instability of underwater acoustic channel, a solution based on recovery resolution decrease is proposed. Cutting down the recovery resolution will result in reduction of signal sparsity, which leads to better reconstruction quality. At first, the resolution adjusting scheme is proposed. Then the feasibility of reduced resolution recovery is studied. Then a data quality evaluation index based on recovery error and resolution is proposed. According to the data quality factor, a resolution adaptive adjusting scheme is designed. For a given observe measurements, the proposed scheme adjusts the resolution adaptively to obtain the recovered data with best quality.Secondly, as the basis of underwater acoustic network, underwater acoustic channel has become a research hot spot for its complexity. The energy consumption feature of underwater acoustic channel is studied in this thesis. The feature of channel attenuation, noise and bandwidth are analyzed. Model of transmission energy consumption is proposed. Then on the basis of the designed model, analysis of the optimal transmission frequency and distance in terms of energy efficiency is proposed.Thirdly, an energy efficient routing protocol in three dimension underwater acoustic network is presented. Three existing routing protocols are analyzed and simulated, which are hierarchical routing VAPR, tree structure routing 3DIAIR and cluster routing New LEACH. Combining the merits of these protocol, the Hybrid LEACH routing protocol is proposed. Aiming at decreasing the network energy consumption and prolong the network lifetime, the parameter setting is analyzed. Meanwhile, the observation matrix design and sub-network reconstruction approach based on compressed sensing and routing protocol are proposed.Finally, integrating the adaptive-resolution data recovery and routing protocol, an underwater acoustic network information collecting system based on compressed sensing is proposed. Parameters which effect system performance such as reconstruction precision, resolution and network lifetime are analyzed and simulated, then the system adaptive adjustment scheme is determined. The scheme takes network energy consumption and reconstruction quality into consideration, and adjusts each parameter to modify the reconstruction and routing protocol, so as to achieve longer network lifetime on the premise of moderate resolution and reconstruction precision.