[time]
2020-12-02T13:29:35+01:00

[team_name]
CorNav

[team_institution]
National University of Defense Technology

[logolink]


[system_name]


[website]


[track]
4

[reference_person]
langping an,mang wang,zheming tu,cahoqun chu,ze chen, shufang zhang

[email]
anlp_gfkd@163.com

[description]
Strapdown inertial navigation based on zero-velocity detection is a typical method of pedestrian navigation. The traditional threshold adjustment method based on condition judgment has poor robustness to different movement patterns, and it is hard to realize automatic adjustment and precise navigation in the multi-movement state. We propose a pedestrian indoor navigation algorithm based on the adaptive threshold, magnetic heading calibration, motion pattern recognition, and altitude estimation driven by data. First, we carry out the magnetic calibration and determine the initial parameters according to the initial data, Then, we detect the zero-velocity interval based on LSTM, which is fused with the navigation trajectory solution model in KEF.  What's more, we calibrate the heading with a magnetometer. Finally, we use a data-driven algorithm for height estimation. 

[references]