Neyman-Pearson criterion-based zero speed detection method

Abstract

The invention discloses a Neyman-Pearson criterion-based zero speed detection method, which comprises the following steps of receiving measured information output by sensors in real time during footstep motions in a single-soldier navigation system by using a handheld computer; determining a window function N according to system sampling frequency and data transmission speed; converting a zero speed detection problem into a modeled mathematical problem by utilizing a double-hypothesis testing theory, and obtaining a Neyman-Pearson criterion-based zero detection inequality; determining mathematical models of output signals of miniature inertia measurement unit sensors and received signals of the handheld computer; calculating a joint probability density function of the output signals of the miniature inertia measurement unit sensors; replacing unknown elements in the inequality with maximum likelihood estimation values of unknown signal elements to obtain an extensive probability likelihood ratio inequality; and substituting the output data of a miniature inertia measurement unit into the extensive probability likelihood ratio inequality, and further detecting a zero speed state. According to the method, problems are mathematized and modeled, and the detection accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of zero-speed detection of an individual soldier's autonomous navigation system, and in particular relates to a zero-speed detection method based on the Neyman-Pearson criterion. Background technique [0002] When the individual navigation autonomous positioning device based on the inertial calculation of 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. The results of dead reckoning have verified that in the navigation stage, if the error of the MEMS inertial device cannot be effectively compensated, the position error will diverge with the trend of the cube of time, and the system will eventually lose its navigation function. Therefore, the inertial calculation algorithm of the MEMS is applied to The biggest difficulty of the individual navigation system is to design an effective erro...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the embodiments of the present invention is to provide a zero-speed detection method based on the Neiman-Pearson criterion, aiming to solve the problem of poor stability and low accuracy in the existing zero-speed detection method, which leads to poor navigation accuracy after zero-speed correction. Low, it is difficult to meet the requirements of accurate and reliable individual navigation

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