Abstract
The foot-mounted inertial navigation system is an important method of pedestrian navigation as it, in principle, does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial pedestrian navigation aided with both ZUPT (zero velocity update) and the range decomposition constraint performs better than those in their own respective methods. This paper recommends that the separation distance between the position estimates of the two foot-mounted inertial navigation systems be restricted by an ellipsoidal constraint that relates to the maximum step length and the leg height. The performance of the proposed method is studied by utilizing experimental data, and the results indicate that the method can effectively correct the dual navigation systems’ position over the traditional spherical constraint.
Highlights
Positioning and tracking systems have developed over several decades in various applications, ranging from tracking of pedestrians to autonomous vehicles [1]
Increasing attention for the pedestrian navigation problem can be partially attributed to the significant progress in affordable wearable computing platforms and enhancement in sensor quality, especially with respect to micro electro mechanical systems (MEMS) [3]
They set up a dual micro inertial measurement units (MIMU) system with two feet, in which the maximum distance between the two systems is derived from the calibration procedure
Summary
Positioning and tracking systems have developed over several decades in various applications, ranging from tracking of pedestrians to autonomous vehicles [1]. In real-life application, the low-cost inertial navigation systems suffer from the accumulation of errors while calculating the traveled distance of the objects. These errors cause the trajectories to drift away from the actual path as time grows. As shown in [8], the use of the two-feet range constraints can significantly improve the navigation performance and a 110 m straight-line experiment showed that the spherical constraint algorithm can reduce the mean error and covariance of the final position estimates. In [9], the authors proposed a method for a dual-mounted INS to reduce the systematic heading drift They set up a dual MIMU system with two feet, in which the maximum distance between the two systems is derived from the calibration procedure. In this paper we take into account different separation constraints in level and height directions, which is shown to be more effective to correct the pedestrian location
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