3D WSN Localization Algorithm Based On Constraint Particle Swarm Optimization

Wireless Sensor Network (WSN) is a new ad-hoc network technology whichcombines sensor technology, wireless communication, Micro-Electro-Mechanismsystem and embedded technology. In WSNs, lots of sensor nodes work cooperativelyto gather and process information in real-time, and send the results to network users.This technology can be widely applied in military applications, environmentmonitoring, smart home, intelligent transport system and other commercialapplications.The information collection technology in WSNs, it often associated with the nodelocalization technology, as there is no sense in practical applications without nodeposition information. By now, most of positioning algorithms are based ontwo-dimensional space. But in practice, the distribution of nodes is discussed in thecomplex three-dimensional space. Therefore, it’s a hot point to discuss the locationalgorithm in three-dimensional space.This paper firstly states the concept of WSN and the basic positioning algorithms.Secondly, on the basis of Received Signal Strength Indicator (RSSI), we mainlydiscussed two positioning algorithms in three-dimensional space. The first algorithmis on the basis of traditional positioning algorithm, we put forward TaylorWeighted-Least-Squares (Taylor-WLS) positioning algorithm. Another algorithm isthe Constraint Particle Swarm Optimization (CPSO) positioning algorithm, which ison the basis of Particle Swarm Optimization (PSO), and introducing the penaltyfunction thought in dealing with constraint problem.Finally, these two positioning algorithms are validated by MATLAB simulationexperiments from four factors: node density, anchor node density, distance radius andranging error. This shows that CPSO positioning algorithm is superior to Taylor-WLSin different degree, CPSO has more robust against errors, better convergence and lesshardware investment, etc.