Abstract
Foot-mounted inertial pedestrian positioning (FIPP) plays an important role for facilitating pedestrian activities. It is suitable for indoor environment applications where global navigation satellite systems are unavailable such as during firefighting and military actions. However, the positioning error of FIPP can increase rapidly due to the measurement noise of the sensors. Zero Velocity Update (ZUPT) is an error correction method proposed to solve this accumulative error. However, the heading misalignment angle, which results in a continuous increase in the positioning error, cannot be estimated by ZUPT. In order to solve this problem, the improved ZUPT based on the Improved Attitude Algorithm (IAA) according to accelerometer measurements is proposed in this paper. When a pedestrian is in the stance phase, the horizontal attitude is estimated by using accelerometer measurements. According to the relationship between the heading misalignment angle and horizontal attitude, the heading misalignment angle is obtained by a series of mathematical derivations. By taking the velocity error and the attitude misalignment angle as observations, the heading misalignment angle and positioning error can be estimated and compensated for through the Kalman filter. Finally, we use MTI-G710 sensor manufactured by XSENS for the actual test and the experiment results show that the proposed method is effectively correct.
Highlights
The Foot-mounted inertial pedestrian positioning (FIPP) is autonomous and unaffected by the external environment
The analysis shows that Zero Velocity Update (ZUPT) can reduce the velocity error, Electronics 2019, 8, 1405; doi:10.3390/electronics8121405
For FIPP, pedestrian positioning information can be obtained by calculating the angular velocity and the linear velocity of the foot movements measured by Micro Inertial Measurement Unit (MIMU) in real time
Summary
The Foot-mounted inertial pedestrian positioning (FIPP) is autonomous and unaffected by the external environment. In ZUPT, the velocity error is taken as the observation to estimate the navigation error caused by inertial sensors measurement noise using the Kalman Filter [14,15,16,17]. Many papers are devoted to solving the magnetic interference problem and have obtained optimized results [36,37] These methods cannot be used as a magnetic interference compensation scheme during the pedestrian positioning process because of their long calibration times (more than 20 s). In line with the problems above, an improved foot-mounted MIMU pedestrian positioning method is proposed in this paper. Based on accelerometer measurements without any other external sensors, which was aimed at solving the heading misalignment angle that cannot be observed by ZUPT. It is used to solve the problem that the traditional ZUPT method cannot estimate the heading misalignment angle.
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