An enhanced positioning scheme for chirp spread spectrum ranging

In this paper, we propose an algorithm for acquiring enhanced position coordinates when using the chirp spread spectrum (CSS) specified in IEEE 802.15.4a. Because the measured distances are generally perturbed by measurement noise, the extended Kalman filter (EKF) can be applied to trilateration to treat the variation in the measured distances due to the noise. In practice, the average value of many measured distances obtained using the CSS is not equal to the true distance, because the noise in the measurement has a nonzero mean; that is, a nonzero average error exists. Because the EKF is only suitable for a case with zero mean noise, the average error needs to be eliminated in advance. For this purpose, we propose a minimization criterion that determines weighting parameters. The average error is reduced by multiplying measured distances by the weighting parameters. To verify the performance of the proposed method, we conduct experiments for the CSS-based positioning of given targets, and compare the results for the EKF with and without the proposed algorithm. From the results, we can find that the coordinates estimated by the EKF with the proposed algorithm are more accurate.