Indoor Personal Navigation System Based on Zero Velocity Detection of Pseudo Adaptive Threshold

To limit error growth of the indoor navigation system(INS),according to the walking regulars,based on personal multi-gait modes,a zero velocity detection of pseudo-adaptive threshold value was studied.Through the acceleration variance and the sum of the squares of the gyro modulus value as a test basis,a sliding time window was set to determine the movement patterns for adjusting the size of the threshold,and the testing results was stable and reliable for run,walk and step.Because the course angle is unobserved,the Kalman zero velocity correction algorithm cannot modify the course angle.Using the particle filter algorithm of fusing indoor maps,the particle weight across the wall is zero.For larger error data,the particle degeneration phenomenon can be effectively avoided by using the method of adaptive resampling.The experimental results show that when the speed is within 3 m/s,the zero velocity detection accuracy attains more than 97%.After using the particle filter algorithm of fusing indoor maps,about 210 m distance to walk normally,the indoor positioning error decreases from the original 2.3 m down to 0.2 m.