3 research outputs found
Improvement of a Low Cost MEMS Inertial-GPS Integrated System Using Wavelet Denoising Techniques
In this paper, the wavelet denoising techniques using thresholding method are applied to the low cost micro electromechanical
system (MEMS)-global positioning system(GPS) integrated system. This was done to improve the navigation performance. The
low cost MEMS signals can be distorted with conventional pre-filtering method such as low-pass filtering method. However,
wavelet denoising techniques using thresholding method do not distort the rapidly-changing signals. They can reduce the
signal noise. This paper verified the improvement of the navigation performance compared to the conventional pre-filtering by
simulation and experiment.DAPA/ADD/NGR
A Movement-Classification Algorithm for Pedestrian using Foot-Mounted IMU
In this paper we present a PDR (Pedestrian Dead Reckoning) algorithm which uses characteristic features to identify different motions and eventually develop a classification algorithm for such motions. We used a single IMU sensor which imbedded at the pedestrians right foot. PDR is a device which provides position information of the pedestrian. Possible area of application for PDR is detecting the motions of rescuers or squads and locating their real-time spatial coordinates to enhance their rescuing and escaping. However, PDR in its original configuration and algorithm is not able to differentiate distinct motions such as running from plain walking, a function is required to accurately detect the motion of firefighters, who frequently crawl, climb up and down, squat, and run depending on the situation. Thus, we developed an algorithm for distinguish such motions using some significant features. Some tests are conducted in laboratory and verified result of our algorithm.NAPsupported by a grant from Korea Research
Council of Fundamental Science & Technology funded
by Ministry of Education, Science and Technology in
2011. [Project: A Study on Satellite based Position
Tracking Technology for Calamity Prevention and Public
Safety Improvement