A Zero Speed ​​Detection Method Based on Neiman-Pearson Criterion

Abstract

The invention discloses a zero-speed detection method based on the Neiman-Pearson criterion. The method includes: receiving the measurement information output by the sensor when the footsteps are moving in the individual soldier navigation system in real time with a hand-held palm computer; according to the system sampling frequency and data transmission Determine the window function N of the speed; use the double hypothesis test theory to transform the zero-speed detection problem into a modeled mathematical problem, and obtain the zero-speed detection inequality under the Neiman-Pearson criterion; determine the output signal of the miniature inertial measurement unit sensor and the handheld computer The mathematical model of the received signal; obtain the joint probability density function of the output signal of the miniature inertial measurement unit sensor; use the maximum likelihood estimation value of the unknown signal element to replace the unknown element in the zero-speed detection inequality to obtain the extensive probability likelihood ratio inequality; the miniature The inertial measurement unit output data is substituted into the extensive probability-likelihood ratio inequality to detect the zero-velocity condition. The invention makes the problem of the detection method mathematized and modeled, and improves the detection precision.

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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