Simulation of foot-mounted IMU signals for the evaluation of PDR algorithms

A common problem in the evaluation of Pedestrian Dead Reckoning (PDR) algorithms is the determination of a good ground truth. Some authors propose the use of external motion capture systems, however, their setup, complexity, synchronization and limited coverage are important limitations. We propose the generation of a simulated IMU signal for pedestrians, that is obtained from a given 3D trajectory (position and attitude). The trajectory can be artificially generated or based on a real human walk pattern. This information can be used as a ground truth for the identification of systematic errors, or to obtain a statistical analysis of the effect of any noise added to the simulated signal. Any specific IMU can be simulated by adding its characteristic error pattern, and modifying them, the most influential IMU characteristics can be determined, and if possible minimized. We tested a PDR method based on an Inertial Navigation System (INS) using an Extended Kalman Filter (EKF) with a noiseless IMU signal. Since failures were detected in the stance phase, we proposed and tested some improvements. The influence of adding specific error patterns to the IMU signal were determined measuring their effect on the evolution of the standard deviation of the position error over time. The most influential source of error for an INS mechanization is the bias in the gyroscope, however the EKF-based PDR algorithm showed to diminish in a significant way many of the positioning errors. The IMU-simulation method is proposed as a way to compare several algorithms and to test new PDR improvements during algorithm design.