Centroid algorithm, as relatively simple, depends upon the connectivity of WSN and nodes density, in which the error of node orientation is high, the calculation for the minimum error is too large and the time which it takes too long. In this paper, centroid algorithm is improved by weighted vector to enhance precision of node localization, at the same time, particle swarm optimization is used to fast the speed of convergence. As is shown in the simulation results, compared with the least square method, our new algorithm has higher positioning accuracy and decreases rapidly with few cycles.
Keywords-centroid algorithm; weighted vector; PSO; least square method
I. INTRODUTIONWireless sensor networks (WSN) have gained worldwide attention in recent years, particularly with the proliferation in Micro-Electro-Mechanical Systems (MEMS) technology which has facilitated the development of smart sensors. These sensors are small, with limited processing and computing resources, and they are inexpensive compared to traditional sensors. These sensor nodes can sense, measure, and gather information from the environment and, based on some local decision process, they can transmit the sensed data to the user [1].Localization, for a sensor to determine its location information has become an attractive research issue in WSN. Much previous research has proposed numerous localization schemes, which are generally classified into range based and range-free localization schemes, depending on the use of distance (range) or angle estimate [2]. GPS is a wide-area system for sensor localization, but extremely expensive and energy-consuming properties make it impractical to be installed in a sensor. Other range based schemes, including RSSI, AoA and ToA/TDoA approaches achieve sensor positioning, but have constraints in hardware cost (e.g., GPS receiver or smart/directional antenna).Unlike the range-based technique, the range-free scheme enables sensors to learn their location information without the aid of range estimates. Such techniques, like APIT [3], and MDS [4], DV-hop [5] generally require numerous 2011 Fourth International Symposium on Computational Intelligence and Design 978-0-7695-4500-4/11 $26.00