ArticleApplied bionics and biomechanics2024
SHAKF-PU: Sage-Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning.
Article in Applied bionics and biomechanics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Adaptive Trajectory-Constrained Heading Estimation for Tractor GNSS/SINS Integrated Navigation.Sensors (Basel, Switzerland) · 2026Article
- Designing of Airspeed Measurement Method for UAVs Based on MEMS Pressure Sensors.Sensors (Basel, Switzerland) · 2024Article
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Abstract
Step length estimation (SLE) is the core process for pedestrian dead reckoning (PDR) for indoor positioning. Original SLE requires accurate estimations of pedestrian characteristic parameter (PCP) by the linear update, which may cause large distance errors. To enhance SLE, this paper proposes the Sage-Husa adaptive Kalman filtering-based PCP update (SHAKF-PU) mechanism for enhancing SLE in PDR. SHAKF has the characteristic of predicting the trend of historical data; the estimated PCP is closer to the true value than the linear update. Since different kinds of pedestrians can influence the PCP estimation, adaptive PCP estimation is required. Compared with the classical Kalman filter, SHAKF updates its
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