Heading Estimation Algorithm Based on Region Partition Particle Filter for Pedestrian Navigation

Dead reckoning has a significant purpose in pedestrian navigation algorithms with assumption of accurate heading estimation. This paper proposes a heading estimation on real time compensation on the basis of region partition particle filter for pedestrian navigation system (RPPF). The RPPF algorithm computes heading correction in real-time using a particle filter. It establishes a functional relationship between the movement of stochastic pedestrian and the regular hexagonal heading constraint; afterwards, it realizes the heading compensation with hexagonal constraint and enhances the heading accuracy. In order implement the proposed algorithm, we conducted a walking experiment of closed curves; the comparative result with the traditional strap-down attitude algorithm, the RPPF enables the effective reduction in the heading error and truly reflects the trajectory curve of pedestrian. The positioning error of the RPPF is less than 2% of the travel distance, which can meet the positioning requirements of pedestrian.