Adaptive step length estimation algorithm using optimal parameters and movement status awareness

An adaptive step length estimation algorithm operating with optimal parameters and a movement status awareness algorithm are proposed. The proposed algorithm was developed as a means for increasing the accuracy in estimating walking distances. The algorithm was applied to pedestrian navigation system, ubiquitous health monitoring systems, and so forth. The algorithms optimal parameters were derived after measurement errors were taken into consideration. The movement status awareness algorithm was designed using a walking characteristic called the acceleration variance. After estimating a subjects walking distance using the proposed algorithm, the measured error was 4.8% with respect to actual walking distance. Alternatively, estimating a subjects walking distance without the algorithm yielded an error of 20% with respect to actual walking distance.This research was supported in part by ASRI (Automation & Systems Research Institute) and MEMS Research Center for National Defense funded by Defense Acquisition Program Administration