Discrete wavelet multiscale analysis based random error compensation method for MEMS (Micro Electro Mechanical system) gyroscope

Abstract

The invention discloses a discrete wavelet multiscale analysis based random error compensation method for an MEMS (Micro Electro Mechanical system) gyroscope, and the method is used for improving the data measurement accuracy of the MEMS gyroscope. The method comprises the following steps: decomposing a signal of the MEMS gyroscope by using a binary orthogonal discrete wavelet Mallat algorithm step by step, wherein the decomposing scale comprises 3 levels and a decomposed approaching signal and a decomposed detail signal are subjected to time series modeling and kalman filtering after the first level is decomposed; performing the second-level decomposing on the filtered approaching signal and then gradually decomposing and filtering in the same manner. The filtered approaching signal at the final layer and the various detail signals are subjected to signal reconstruction. According to the discrete wavelet multiscale analysis based random error compensation method for the MEMS gyroscope, the random error compensation effect of the MEMS gyroscope is improved, and the method has an important role for a vehicle-mounted or ship-based measurement occasion requiring high accuracy, high efficiency and high stability.

Description

technical field [0001] The invention belongs to the field of signal processing, and relates to a MEMS gyroscope data processing method, in particular to a MEMS gyroscope random error compensation method based on discrete wavelet multi-scale analysis. Background technique [0002] MEMS technology is an emerging technology field developed in the past 20 years. Micro-mechanical angular velocity sensor (gyroscope) is a miniature angular velocity sensor manufactured by micro-machining technology. It is a world-leading technology integrating new technologies such as micro-precision machinery, microelectronics, and semiconductor integration technology. Its appearance has brought about a new leap in inertial technology. At the same time, the increasing market demand for new vibration angular velocity sensors with small size, low price and reliable performance has greatly promoted the development and research of such sensors. Due to the limitations of current microfabrication and o...

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Problems solved by technology

But it is worth noting that when the Mallat algorithm in the most commonly used wavelet analysis is used to decompose the signal, the signal will be down-sampled after passing through the high-pass filter and the low-pass filter. That is, the second decimation process, and then the detailed signal and the approximation signal of the signal will be obtained. According to the Nyquist sampling theorem, downsampling will introduce signal distortion. This distortion is called aliasing. If it is not processed in time, the effect of aliasing will be reduced. influence, the effect of wavelet denoising will be reduced

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