The Research On Optimization Method For Location Accuracy Of Wireless Sensor Network

Wireless Sensor Network, which is one of the key technologies of the Internet of Things,and can be widely applied in agriculture, environmental monitoring, intelligent household andtarget tracking. Meanwhile, it is of important academic significance and realistic value to studyon the Location Based Services. This paper mainly studies the wireless location technology. Themain task includes the following aspects:It does researches on the structure and characteristics of the network, application and the keytechnologies, research status of WSN. Based on this, the paper mainly introduces several typicalRange-Based and Range-Free localization algorithms.It focuses on the application of the intelligent algorithm in location technology. A methodusing modified shuttled frog leaping algorithm to improve the location accuracy of the DV-Hopalgorithm is proposed. First, the unknown nodes are located by foregoing algorithm and thelocalization mechanism is transformed into solving a nonlinear least squares model. Then, theweighting factors and fitness function are chosen according to the analysis of location errors. Atlast, modified shuttled frog leaping algorithm with chaos mapping and Cauchy mutation is usedto optimize the position of the unknown nodes. The experiments show that the algorithm is notonly more simple and reliable, but it also improves the location accuracy.It studies the TDOA localization algorithm. In order to resolve the problem of NLOSpropogation, a new type of quantum BP neural network is put forward to modify the locationdata. The neural network is of quick learning ability, fast convergence rate and good robustness.Then, combine the neural network with classical Least Squaers method, and finally the locationof the nodes is calculated. The simulation results show that the algorithm reduces the positioningerror significantly compared with Taylor and Chan algorithm.