Asynchronous UWB and camera fusion for delta operator-based indoor positioning under information loss

In this paper, an asynchronous information fusion issue is investigated for indoor positioning of an unmanned ground vehicle equipped with an ultra-wideband (UWB) positioning system and a camera. A local UWB estimator with a fixed sampling period is developed based on a delta operator Kalman filter. A local camera estimator is designed using a distinct fixed sampling period under information loss. To address the asynchronous sampling challenge among different sensors, a delta operator approach is introduced into a matrix-weighted fusion algorithm to obtain a comprehensive fusion estimator. Rigorous convergence analysis for both local estimators and the fusion estimator is conducted for the indoor positioning system. The effectiveness of the proposed asynchronous information fusion method is validated through experimental testing on an Ackermann vehicle.