Conference Paper

Performance characterisation of foot-mounted ZUPT-aided INSs and other related systems

Signal Process. Lab., KTH R. Inst. of Technol., Stockholm, Sweden
DOI: 10.1109/IPIN.2010.5646939 Conference: Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on
Source: IEEE Xplore


Foot-mounted zero-velocity-update (ZUPT) aided inertial navigation system (INS) is a conceptually well known with publications in the area typically focusing on improved methods for filtering and addition of sensors and heuristics. Despite this, the performance characteristics, which would ultimately justify and give guidelines for such system modifications of ZUPT-aided INSs and other related systems, are in some aspects poorly documented. Unfortunately, the systems are non-linear, meaning that the performance is dependent on the system set-up, parameter setting, and the true trajectory. This complicates the process of evaluating performance and partially explains the few publications with detailed performance characterisation results. Therefore in this article we suggest and motivate methodologies for evaluating performance of ZUPT-aided INS and other related systems, we apply them to a suggested baseline set-up of the system, and study some aspects of the performance characteristics.

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Available from: Peter Händel, Mar 02, 2014
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    • "In the former one, IMUs attached to certain part of the body or mounted on the shoe provides accelerometer readings along the direction of walking and the data are double integrated to obtain the travelled distance. ZUPT[4]or self-resetting[10]algorithms are developed to reduce the accumulated error caused by sensor drift and noise. Recently, many PDR systems are developed on commercial off-the-shelf smartphones using step-detection based methods. "
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    ABSTRACT: This paper proposes an approach for pedestrian tracking using dead reckoning on a standard smartphone. Previous studies report tracking pedestrians when the mobile device is carried in a defined way within the tracking period. This paper presents a new approach which extends and enhances previous methods by identifying three typical modes of carrying the device during walking and using that fact to enhance tracking accuracy. Based on the real-time identification of modes, a light-weight step based tracking algorithm is developed with a novel step length estimation model. The tracking system is implemented on a commercial off-the-shelf smartphone equipped with a built-in Inertial Measurement Unit. It achieves real-time tracking and localization performance with typically sub-meter error.
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    • "As a result, no universal parameters can be given. However, some groups of parameters can still be identified [11]. The parameters of the hardware set-up are only the sensor placement/mounting and the sampling frequency. "
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    ABSTRACT: Foot-mounted inertial measurement units (IMUs) are becoming the basis for many pedestrian positioning systems as a component of accurate indoor navigation. However, most of solutions that implement low-cost IMUs are often connected to a laptop by a wired connection which interferes with the pedestrian movements. Moreover, nobody walks carrying a laptop but a smartphone. Smartphones are attractive platforms for researchers to collect data coming from several sensors due to their small size, low-cost, and the fact that they are already carried routinely by most people. Therefore, this paper (i) describes a custom-built foot-mounted pedestrian indoor localization system based on commercially available low-cost inertial sensors connected wirelessly (via Bluetooth) to a smartphone, and (ii) demonstrates the capability of smartphones to be used as the target of a wirelessly IMU-based positioning system where raw IMU data will be processed in real time. We have tested the pedestrian tracker with commercial devices in a five floor building with reasonable results (accumulated error lower than 1%).
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    • "However, some groups of parameters can still be identified. In [10] a classification and study of the parameters is offered. The parameters can be divided into internal parameters and external parameters. "
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    ABSTRACT: The use of foot-mounted inertial measurement units (IMUs) has shown promising results in providing accurate human odometry as a component of accurate indoor pedestrian navigation. The specifications of these sensors, such as the sampling frequency have to meet requirements related to human motion. We investigate the lowest usable sampling frequency: To do so, we evaluate the frequency distribution of different human motion like crawling, jumping or walking in different scenarios such as escalators, lifts, on carpet or grass, and with different footwear. These measurements indicate that certain movement patterns, as for instance going downstairs, upstairs, running or jumping contain more high frequency components. When using only a low sampling rate this high frequency information is lost. Hence, it is important to identify the lowest usable sampling frequency and sample with it if possible. We have made a set of walks to illustrate the resulting odometries at different frequencies, after applying an Unscented Kalman Filter (UKF) using Zero Velocity Updates. The odometry error is highly dependent on the drift of the individual accelerometers and gyroscopes. In order to obtain better odometry it is necessary to perform a detailed analysis of the sensor noise processes. We resorted to computing the Allan variance for three different IMU chipsets of various quality specification. From this we have derived a bias model for the UKF and evaluated the benefit of applying this model to a set of real data from walk.
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