Novel calibration method for improved UWB sensor distance measurement in the context of application for 3D analysis of human movement

Abstract

Integrated UWB and MIMU sensor systems have become popular for pedestrian tracking and indoor localization, since this facilitates data fusion that improves position estimation accuracy by exploiting the complementary nature of their error sources. Integrated UWB/MIMU sensors also have great potential in only on-body use for 3D analysis of human movement, as with MIMU sensors alone accurate direct estimation of (relative) body segment position is not possible. For this, a position estimation accuracy with errors smaller than 1 cm is deemed required. The lowest position estimating error with integrated UWB/MIMU systems, reported so far, is around 5 cm. The main accuracy limiting factors were found to be the systematic errors in the distance estimates from the UWB sensor. Multiple reported attempts to calibrate for these systematic errors failed to achieve the desired accuracy. This article presents a novel distance-bias calibration method that minimizes the residual systematic distance estimate errors using multiple sensors in a swarm configuration. Validation was performed against synthetic reference data and against reference data measured with an optical motion tracking system. Significantly reduced systematic distance estimate errors (≤0.5 cm) were found. These results promise to facilitate significantly better position estimates in future UWB/MIMU data fusion.