Abstract
Using an MEMS Inertial Measurement Unit (MEMS IMU) array mounted on foot is a feasible approach to improve the pedestrian tracking accuracy for the pedestrian navigation system (PNS). Based on the in-house developed IMU array, the paper proposes a new integrated framework that combines adaptive deck reckoning (ADR) with the modified zero velocity update (ZUPT). In the proposed ADR algorithm, the IMUs with large drift errors on the array are selected and removed according to the step length and the track angle computed by each IMU on the array. Then, by using the step length and the track angle of each step computed by remaining IMUs, the foot position extracted from the traditional ZUPT model is estimated on the basis of least squares (LS) so as to improve the traveled distance calculation accuracy. Compared with the traditional IMU array fusion method based on a maximum likelihood estimator (MLE) when it is used in the PNS, which is approximately taking the mean value of array readings, the proposed method is equivalent to adaptively fusing the array readings and thus improves the pedestrian tracking accuracy. To compare the proposed method with MLE, two different types of walking tracks are designed. The 161 m straight line experiments show that the end position by ADR/modified ZUPT method is much closer to the one of the reference trajectory compared with the MLE in repeated walks, and the closed-loop tracks about 300 m show that the positioning error with respect to the total traveled distance is less than 0.6% (1σ), which is higher than 1% (1σ) of MLE.
Highlights
Pedestrian navigation systems (PNS) have drawn much attention in recent years because they can be of significant use in applications for both civilian and military [1,2], especially in indoor environments where GPS-like satellite external positioning is degraded or unavailable [3,4,5].Pedestrian navigation technologies can be divided into two sorts: the infrastructure-based positioning technology and the infrastructure-free navigation solutions [6,7]
On the basis of least squares (LS), step length and track angle of each step are estimated synthetically by using that computed by remaining inertial measurement unit (IMU); every step position of the pedestrian is calculated through the proposed adaptive deck reckoning (ADR) algorithm, firstly, IMUs with large drift errors are selected and removed according to the step length and the track angle computed by every IMU in the array during a zero velocity update (ZUPT) period
We give a brief description of the in-house developed MEMS IMU array in the differences between the MLEintegrated based on algorithm the traditional and the proposed
Summary
Pedestrian navigation systems (PNS) have drawn much attention in recent years because they can be of significant use in applications for both civilian and military [1,2], especially in indoor environments where GPS-like satellite external positioning is degraded or unavailable [3,4,5]. The foot-mounted IMU and radio frequency identification (RFID) measurements tightly coupling method proposed in [28] places several active RFID tags at known locations in a building and corrects the diverging position error by the received signal strengths (RSSs) Such an aided method faces the same problem as the infrastructure-based positioning technology, that is, RFID tags would be damaged in a few complex and hostile environments and be unable to be used. On the basis of least squares (LS), step length and track angle of each step are estimated synthetically by using that computed by remaining IMU; every step position of the pedestrian is calculated through the proposed ADR algorithm, firstly, IMUs with large drift errors are selected and removed according to the step length and the track angle computed by every IMU in the array during a ZUPT period. The of the ADR/ZUPT integrated framework based on the adaptively fusing foot-mounted IMU array
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