Mthod for compensating temperature error of micro-electromechanical inertial measurement unit

Abstract

The invention discloses a method for compensating a temperature error of a micro-electromechanical inertial measurement unit. The method comprises the following steps: designing a full-temperature experiment and collecting full-temperature output data; according to the output data of the full-temperature experiment, analyzing the temperature output characteristics of the MIMU, and selecting temperature variables to establish a temperature error model of an MEMS accelerometer and an MEMS gyroscope; designing an adaptive neural fuzzy inference system; respectively inputting the temperature errors of the MEMS accelerometer and the MEMS gyroscope as training samples into the adaptive neural fuzzy inference system; carrying out trainingby using an adaptive neural network to obtain fuzzy parameters and an acquiringan optimal network model; and calculating prediction outputs of the temperature errors according to the optimal network model, and compensating the full-temperature output of the MIMU by applying a network prediction result. According to the method, a learning mechanism of the neural network enters fuzzy reasoning, so that the temperature error modeling precision is improved, the temperature drift of the MEMS gyroscope is accurately compensated, and the precision of the MIMU in a full-temperature range is realized.

Description

technical field [0001] The invention relates to the technical field of inertia, in particular to an MIMU temperature error compensation method using an adaptive neuro-fuzzy reasoning system. Background technique [0002] At present, as an important application in the field of inertial navigation, the inertial measurement unit (MIMU) based on micro-electromechanical systems has the advantages of small size, low cost, and mass production, and has opened up broad application prospects in strategic military and commercial civilian fields. MIMU, also known as Miniature Inertial Measurement Unit, (Miniature InertialMeasurementUnit, MIMU) is an important MEMS, which is composed of a miniature gyroscope, a miniature accelerometer, an application specific integrated circuit (ASIC), an embedded microcomputer and corresponding navigation software. Provide the position, speed and attitude information of the moving carrier. MEMS is also called Micro-Electro-Mechanical System (MEMS, Micr...

AI Technical Summary

Problems solved by technology

The polynomial model is simple and easy to implement. The temperature error is established as a polynomial linear combination of temperature by using the least square fitting method, which cannot truly describe the nonlinear characteristics of the temperature error, and only considers the temperature input information, which often fails to meet the compensation accuracy requirements; The BP neural network has outstanding learning ability, and it can fit the system model and input-output relationship through the known sample data training of the network, but it has the disadvantages of slow convergence speed and easy to fall into local optimal solution.

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