Table 4 PDR-based navigation systems

Hasan and Mishuk [133]

Data from the accelerometer and gyroscope fused using the Kalman filter

Average deviation: 2 m

(−) The system cannot follow the path of the user if the positioning updates from RF signal are absent for a minimum duration of 5 min

Ju et al. [134]

PDR system with multiple virtual tracking to avoid drift errors in heading angle

Position error: 0.77% of total distance (1430 m)

(+) It solves the limitation of existing methods that assume all of the walls and corridors are parallel or orthogonal

Hsu et al. [136]

Trajectory reconstruction algorithm, Double filter quaternion-based adaptive Kalman filter for sensor fusion

Distance error: 0.52% (5.28 m) of total traveled distance

(+) Reduced the integral error in trajectory reconstruction and estimation without utilizing any other external positioning technique

Liu et al. [145]

Belief propagation algorithm to localize the user by fusing sensory information, and the range information between users

80th percentile of localization error was 1.6 m and 3.5 m

(+) The system is robust towards unknown initial position scenarios and multiple user scenarios

Giorgi et al. [137]

PDR-based navigation system utilizing the embedded sensors of smartphones

Maximum error: 4 steps

(+) Low-cost system

Qiu et al. [141]

Multi-sensor fusion approach using extended Kalman filter

Distance error: 1% of traveled distance

(+) Sensor installation and path propagation errors are rectified

Kuang et al. [142]

PDR approach integrated with magnetic matching

Accuracy: less than 2.5 m

(+) Introduction of magnetic matching approach reduced the drift errors in PDR

Ciabattoni et al. [143]

PDR approach integrated with BLE technology

Distance error: 0.18 m when whole beacons are functioning

(+) BLE beacon-based approach reduced the drift errors in PDR

Shan-Jung et al. [144]

PDR approach integrated with the Wi-Fi fingerprinting technique

Pathway error is almost zero in simulation experiments

Wi-Fi fingerprinting based calibration system reduced the cumulative error in PDR