Zero-speed detection method for individually autonomous navigation system based on hidden Markov model (HMM)

Abstract

The invention discloses a zero-speed detection method for an individually autonomous navigation system based on a hidden Markov model (HMM). The method comprises the following steps: acquiring the output information of a Y-axis gyroscope in a micro inertial measurement unit of the individually autonomous navigation system; preliminarily sectioning the output information of the Y-axis gyroscope according to a function, and performing range division on the sectioned output values of the Y-axis gyroscope; sectioning the output values of the Y-axis gyroscope during the one-step movement of a user, naming the sections, and taking the sections as the state quantities of an HMM process; taking an output range as the output of the HMM to convert a zero-speed detection problem into an HMM decoding problem; acquiring a state transfer matrix A and a matrix B representative of a conversion relationship between an output process and a state process in a one-step movement process of the user; calculating the state quantity Qk of the HMM through Viterbi; and judging a zero-speed interval in the movement process of the user of the individually autonomous navigation system through an inequality. According to the zero-speed detection method, the problems are mathematized and modeled, and the detection accuracy is improved.

Description

Technical field: [0001] The invention belongs to the technical field of inertia, and specifically relates to a zero-speed detection method for a personal autonomous navigation system based on HMM (Hidden Markov Model). Background technique: [0002] When the personal navigation autonomous positioning device based on the Micro Inertial Measurement Unit is working, the error of the inertial device of the Micro-Electro-Mechanical System (Micro-Electro-Mechanical System) diverges seriously. If the error of the inertial device cannot be effectively compensated, the position error will be as follows: The trend of the time cube diverges, and the system will eventually lose its navigation function. Therefore, the key to applying MEMS inertial measurement components to personal navigation systems is to design effective error correction algorithms. Zero-speed correction is an effective error compensation algorithm. The speed value obtained by the navigation solution when the user of t...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a zero-speed detection method based on HMM (Hidden Markov Model) for personal autonomous navigation system, aiming to solve the problem of poor stability, low accuracy, large amount of calculation and long time-consuming of the existing zero-speed detection method The navigation accuracy after zero-speed correction is low, and it is difficult to meet the requirements of accurate and reliable personal navigation

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