Localization Using Saw Rfid Sensor Based on Kalman Algorithm

As surface acoustic wave (SAW) sensor has wireless and passive characteristics , the traditional time-of-flight location method is greatly affected by the path loss, and thus the location accuracy is low. In order to improve the location accuracy, a Kalman algorithm considering path loss is proposed. Combining with the path loss model, the relationship between the variance of location error and the detection distance is derived. Based on this relationship, the observation equation of the Kalman algorithm is modified, and also the Kalman algorithm with noise variance varying with distance is obtained. The simulation results show that the location variance of the traditional location algorithm is 0 ~ 1.78cm when the detection distance is within 1.5m, and the location variance of this method is 0 ~ 0.41cm. Compared with the traditional location algorithm, the accuracy of this method improves about 4 times, which verifies the reliability of this algorithm.