Abstract
In this paper, a smoothing algorithm for compensating inertial sensor saturation is proposed. The sensor saturation happens when a sensor measures a value that is larger than its dynamic range. This can lead to a considerable accumulated error. To compensate the lost information in saturated sensor data, we propose a smoothing algorithm in which the saturation compensation is formulated as an optimization problem. Based on a standard smoothing algorithm with zero velocity intervals, two saturation estimation methods were proposed. Simulation and experiments prove that the proposed methods are effective in compensating the sensor saturation.
Highlights
IntroductionThere are many ways to estimate the trajectory of a moving object
In motion tracking, there are many ways to estimate the trajectory of a moving object
This paper has proposed some approaches to compensate for sensor saturation
Summary
There are many ways to estimate the trajectory of a moving object. In [2], Lee and Grimson investigated person identification and gender classification based on moments computed from the silhouette of walking people. These camera systems are limited in their setup ranges and sometimes have high implementation costs. The angle views of the cameras are limited and they are Sensors 2014, 14 affected by illumination. Due to these reasons, for long distance or outdoor measurements, motion tracking based on camera systems seems to be a difficult task
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