Method of pedestrian navigation based on robust filter

Since the positional method of pedestrian navigation system (PNS) is usually assisted by global positioning system (GPS) and dead reckoning (DR) system integrated navigation algorithm, the PNS positional accuracy tend to be diminished by the GPS positional errors, especially positional outliers. To reduce the tendency and improve the accuracy of the pedestrian navigation system, a method of GPS and DR integrated navigation algorithm based on robust filter is presented. The Kalman filter model of PNS is obtained through modeling DR systematic errors and DR sensor errors first. Then, the positional difference between GPS and DR is used to estimate the extent to which the latest observation error meets their prior statistics. Based on the extent, the observed weight is renewed by an equivalent weight to restrict the negative effect of GPS positional error on integrated navigation. Finally, the result of real data from the experimental prototype shows that, in the case of GPS performing badly, the robust method is much more effective than Kalman filter in reducing the influence of the GPS positional error and could improve the positional accuracy by about 5 m. Thus, the positional accuracy of PNS based on GPS/DR integrated navigation is improved without additional hardwares.