Energy-Aware Error Correction Method for Indoor Positioning and Tracking

Indoor positioning is crucial for the effective use of drones in smart environments, enabling precise navigation and control in complex indoor spaces where GPS signals are weak or unavailable and wireless communication-based systems must be used. In order to improve positioning accuracy, various distance measurement techniques and related error correction methods have been proposed in the literature. However, these methods are mostly focused on accuracy and often require a significant amount of computational resources, which is quite inefficient when deployed on battery-operated devices like small robots or drones because of their limited battery capacity. Moreover, conventional error correction methods are little effective for the tracking of moving objects. In this paper, we first analyze the trade-off between energy consumption and accuracy for the error correction and identify the most energy-efficient error correction method. Based on this analysis in the accuracy/energy space, we introduce a new energy-efficient error correction method that is especially targeted for tracking a moving object. We validated our solution by implementing an Ultra-Wideband based indoor positioning system and demonstrated that the proposed method improves positioning accuracy by 15% and reduces energy consumption by 33% compared to the state-of-the-art method.