Research Of Localization Method Based On Zigbee Wireless Sensor Networks

In recent years, wireless sensor networks gained rapid developmentopportunities, one of the key technologies for wireless sensor network is nodepositioning technology, domestic and foreign scholars have proposed a variety ofapproaches and algorithms. However, the method has certain limitations, such assegmentation of algorithm and error handling are yet to be improved, achievepositioning accuracy also has room to increase.Therefore, to carry out the researchof wireless sensor positioning and improve the positioning precision is of greatsignificance.Aimed at the deficiency existing in positioning algorithm segmentation in theprocess, this paper improved the TLM (Threshold Localization Method) strategypositioning methods, to improve the traditional sensor nodes using single algorithm.In this method, when the node distance less than5m, using the RSSI (ReceivedSignal Strength Indicator) to improve the ranging distance calculation algorithm;When the distance is greater than5m, using the DV-Hop to improve the ranginglocalization algorithm for distance calculation.Aimed at the shortage of error handling in ranging algorithm using leastsquares method in the process of improvement of RSSI-distance data curve fittingprocessing, in the non-locating algorithm improvement processes using DV-Hoplack of connectivity and decentralized nodes in error analysis, error handling sectionas a whole. Finally in the coordinate calculation using the calculation method of theweighted, the closer the node gives greater weight, the closer to the actualcoordinate calculation.We design a wireless sensor network localization system verifies the validity ofthese improved methods, the system consists of hardware and software components.Hardware is composed of sensor nodes, gateways, mobile trolley and uppercomputer, and software by IAR, ZigBee protocol stack Z-Stack Z-Location Engine,position the graphic monitor software and LabVIEW draws a track controlplatform.In the laboratory experiment validation: on a small scale5m5m, the RSSIimproved before and after improvement of the algorithm are verified, it is concludedthat the relative error decreases by13.9%; Within the6m12mscope of thepositioning method for validation of TLM strategy, it is concluded that the relativeerror decreases by22.2%.Experimental results show the TLM strategies more accurately reflect theactual environment with different distance to bring the advantages of differentalgorithms,positioning relative error decreases,and improved the traditional separate using RSSI or DV-Hop positioning of the status of the relative error is bigger.