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

ABSTRACT 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.

0 Bookmarks
 · 
112 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A study of the performance of four zero-velocity detectors for a foot-mounted inertial sensor based pedestrian navigation system is presented. The four detectors are the acceleration moving variance detector, the acceleration magnitude detector, the angular rate energy detector, and a novel generalized likelihood ratio test detector, refereed to as the SHOE. The performance of each detector is assessed by the accuracy of the position solution provided by the navigation system employing the detector to perform zero-velocity updates. The results show that for leveled ground forward gait at a speed of 5 km/h, the angular rate energy detector and the SHOE give the highest performance, with a position accuracy of 0.14% of the travelled distance. The results also indicate that during leveled ground forward gait, the gyroscope signals hold the most reliable information for zero-velocity detection.
    Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on; 10/2010
  • [Show abstract] [Hide abstract]
    ABSTRACT: The localization of an ambulatory individual, a.k.a. a pedestrian, is a quickly-developing domain with the potential to permeate into a variety of applications, as knowledge of an individual's location within an environment becomes ever-more useful. In order to automate the localization task, positioning modules are prime candidates for inclusion in a system. Such modules are expected to reduce both the effort and time incurred during the localization process while improving the accuracy and organization of the exchanged data. Building on and combining recent developments in the fields of step detection using inertial measurement units and structure from motion using a camera rig, the work presented in this paper is an implementation of a pedestrian localization system targeted specifically at infrastructure-less indoor localization. The inertial measurement unit and camera rigs are respectively attached to the mobile user's foot and waist, and the collected data is processed by the localization module to obtain a current position. The focus of this paper is the implementation and preliminary testing of this localization module's components.
    01/2011;
  • Source
    [Show abstract] [Hide abstract]
    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.
    10/2013;

Full-text (2 Sources)

View
9 Downloads
Available from
May 17, 2014