The invention relates to the technical field of
pedestrian indoor positioning, in particular to an arithmetic optimization
algorithm-based finite-state
machine gait detection method, which comprises the following steps of: S1, acquiring
original data such as three-axis acceleration,
angular velocity and the like based on sensor
data acquisition software MATLAB Mobile
software; s2, carrying out
smoothing processing on the
original data through zero offset correction and Kalman filtering; s3, according to a
resultant acceleration change trend in the
gait cycle and in combination with peak and trough threshold constraints, setting an undetermined threshold, and dividing the
gait cycle into a plurality of discrete states; s4, constructing an arithmetic optimization
algorithm by taking the
step number deviation ratio as a
fitness function, quickly obtaining an optimal threshold to be determined, substituting the optimal threshold to be determined into finite-state
machine gait detection, and detecting
pedestrian gait information; and S5, calculating
pedestrian step length and course information based on the gait information, and establishing a motion equation to reconstruct a pedestrian trajectory. According to the technical scheme, the gait detection precision can be remarkably improved, and the adaptability and robustness of pedestrian positioning are effectively enhanced.