Implementation study of a home position monitoring system for marine environment

According to requirements of marine observation environment, a kind of real-time data collection architecture in marine monitoring system, based on wireless sensor network, is proposed in this paper. The architecture is a two-level in-situ monitoring technology: the high level taking GPS as an absolute in-situ and the lower level taking wireless sensor array as a relative in-situ. The buoyages and base station equip with costly GPS, while a large numbers of sensor nodes equip with the cheap RF SOC. In wireless sensors network, we propose a position estimating algorithm that allows sensors to determine their location without any centralized computation. In addition, PEA provides a location verification mechanism that verifies the location claims of the sensors before data collection. We show that PEA bounds the ability of an attacker to spoof sensors´ locations, with relatively low density deployment of reference points. We confirm the PEA against attacks analytically and via simulations. And a novel entropy-based incremental fuzzy clustering algorithm is designed to cluster real-time datum efficiently and gives attention to realtime while improving clustering accuracy by applying a series of improved policies. Results of simulation experiments show that proposed algorithm is adaptive to the requirements of marine observation.