One of the most commonly-used location methods in distance measurements is based on received signal strength(RSS) because this method is cheap for wireless sensor networks.However

its precision in location is easily affected by the interference of the circumstances.This paper employs the principle of the Bayesian chaining rule to thoroughly analyze the probability model of RSS-based distance measurements and set up a more reasonable probability location model based on the principle of maximum likelihood estimation.Considering the characteristics of the transmission of sensor networks

this paper designs an algorithm based on evolutionary algorithm since the model is difficult to work out.Through simulation experiment

the newly established probability location model and the algorithm based on evolutionary algorithm are finally proven to reduce the circumstantial interference and improve the location precision of the sensor nodes.