To reduce the impact of distance information errors

an improved multilateration algorithm named KC-Multilateration is proposed.It is explored that K-means clustering methodology is employed to wireless sensor network localization schemes.By cluster analysis

KC-Multilateration algorithm can figure out the distance data which are far more beyond their true value

and then removes those data from the measured distance data.Then multilateration is adopted with the rest distance data

obtaining the final results.Simulation experiments indicate that the proposed KC-Multilateration can reduce location errors effectively and has more stable location results in a variety of error environment comparing with the original multilateration algorithm.Further experiments based on RSSI indicate that the improved algorithm has smaller location errors and stronger performance of fault tolerance without adding any costs of communication

which verifies effectiveness and practicality of KC-Multilateration.