**7. Summary**

In this chapter, we firstly defined local positioning systems and introduced their applications. Then we presented strap-down inertial positioning techniques covering not only the concepts of dead reckoning and inertial position, but also the algorithms, especially for the rotation of reference frames and the tracking of the orientation of a moving object. We also evaluated the performances of inertial sensors, i.e., gyroscopes and accelerometers and pointed out that the increasing integral drift over time is the main problem affecting the accuracy of positioning. As an example among the efforts to solve this problem, we proposed an approach to integrate pedestrian dead reckoning with inertial positioning in precise tracking, where the characteristics of human gaits are utilized. Magnetic sensors have to be incorporated to update the orientation of moving objects and the relevant algorithm is provided. The experimental study was also included to demonstrate the implementation and the result of positioning. Finally, among existing solutions to enhance the accuracy of local positioning, Kalman filter, EKF and their algorithms are introduced and the examples of their applications are also presented. Magnetic sensors are important resources of data to be fused through Kalman filtering.
