Research On Personal Positioning Technology Based On MIMU With SEMG Aiding

With the increasing demand for indoor, special and unknown environment navigation and positioning, satellite navigation as an important means of current personal navigation field, will lost its power in some complex and special circumstances. In the field of civil, military and deep space exploration, etc., current personal positioning technology cannot meet the needs of engineering practical applications and intelligent trends in the future. To this end, we explore and research the personal positioning technology based on MIMU with SEMG aiding. On the one hand, MIMU and SEMG signals can measure the obvious human movement, on the other hand, SEMG can also measure the non-obvious body movement, or even can sense the human movement intentions to anticipate practical action, provide more directions for personal positioning. Therefore, the paper research on personal positioning technology based on MIMU with SEMG aiding, and the main research work includes the following aspects:(1) Study the basic theory of MIMU personal navigation system, use the quaternion algorithm to calculate the attitude and position. Analyzes the characteristics of SEMG signal and introduce the motor function of lower limb muscles, choose the rectus femoris and gastrocnemius, which have the significant effect on posture control, acquire SEMG signals. After signals de-noising and active segment increased, extracting its MAV, RMS, IEMGp and wavelet characteristic parameters. Through the peak detection calculate the stride frequency, and then based on LM algorithm of BP neural network is proposed. The SEMG characteristic parameters and stride frequency information as input when creating the neural network model, and the actual walking distance divided by actual steps as a standard output.(2) Build the hardware platform of the system, and the MATALAB software is used to acquire data, estimate the step length of SEMG signal, program the SEMG assisted pedestrian dead reckoning algorithm to achieve personal positioning. Presents an easy self-calibration method to implement calibration of the MIMU on a common table only with an inclined surface, no precise turntable is needed. After a series static positions test and rotating test, the error model parameters can be extracted and estimated. To demonstrate the success and the convenience of the calibration method, comparison experiments with the precision turntable have been made, the results show that the accuracy and precision of this method is quite equivalent with the turntable-based calibration.(3) The system was tested indoor and outdoor respectively. Indoor tests shows, walking under normal speed the step error with an order of magnitude always equal or less than 10-4, and the step error of rapid walking is less than 0.01%; Outdoor tests shows, the accuracy of step detection is as high as 99.35%, the maximum step error is less than 0.74%, and the distance error of walk 100 meters in about 80 seconds is less than 1.5%. When walking straight-line, the positioning results with SEMG aiding have effectively compensate the position error and the velocity error, improve the system accuracy. The distance error of walk 60 meters is less than 4.32%.