Abstract
All non-foot-mounted inertial localization systems have a common challenge: the need for calibrating the parameters of the step length model. The calibration of the parameters of a step length model is key for an accurate estimation of the pedestrian’s step length, and therefore, for the accuracy of the position estimation. In a previous work, we provided a proof of concept on how to calibrate step length models with a foot inertial navigation system (INS), i.e., an INS based on an inertial measurement unit (IMU) mounted on the upper front part of the foot. The reason is that the foot INS does not require calibration thanks to the implementation of the strapdown algorithm. The goal of this article is to automatically calibrate the parameters of a step length model of the pocket INS by means of the foot INS. The step length model of the pocket INS has two parameters: the slope and offset of a first-order linear regression that relates the amplitude of the thigh pitch with the user’s step length. Firstly, we show that it is necessary to estimate the two parameters of the step length model. Secondly, we propose a method to automatically estimate these parameters by means of a foot INS. Finally, we propose a practical implementation of the proposed method in the pocket INS. We evaluate the pocket INS with the proposed calibration method and we compare the results to the state of the art implementations of the pocket INS. The results show that the proposed automatic calibration method outperforms the previous work, which proves the need for calibrating all the parameters of the step length model of the pocket INS. In this work, we conclude that it is possible to use a foot INS to automatically calibrate all parameters of the step length model of the pocket INS. Since the calibration of the step length model is always needed, our proposed automatic calibration method is a key enabler for using the pocket INS.
Highlights
Applications based on inertial localization systems have extended from localization in shopping malls or museums [1,2], to safety-critical applications, e.g., tracking a fire fighter’s position [3]
In [17], we provided a proof of concept on how to automatically calibrate step length models with a foot inertial navigation system (INS)
We considered the step length model of a pocket INS, which is an inertial localization system based on an inertial measurement unit (IMU) mounted on the upper thigh
Summary
Applications based on inertial localization systems have extended from localization in shopping malls or museums [1,2], to safety-critical applications, e.g., tracking a fire fighter’s position [3]. The trend is to implement the inertial localization system in a smartphone or in a wearable. A wearable is a device with embedded sensors and a processing unit which can be carried out by attaching it to the body, e.g., a smart watch, or by integrating it in the clothes. Wearables offer an advantage: they can be integrated within the clothes. The miniaturization of sensors, e.g., inertial sensors, will allow for future smart clothing.
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