Abstract
In recent years, the applications of MEMS inertial sensors have expanded significantly. The majority of applications challengesthe accuracy, stability, and sensitivity of inertial sensors. Noise characteristic is a crucial performance indicator for sensors. though diverse methods for analyzing and classifying sensor noise from various perspectives are proposed, t his study examines a prominent noise analysis technique known as Allan Variance (AVAR). According to the results of several computations, this approach classifies inertial sensor noise into five groups. In addition, a set of algorithms are proposed to minimize noise in order to limit sensor noise's impact on the system. In general, these algorithms disregard the type of noise and assume that it is random. In this paper, a quick introduction to these algorithms will be provided. A comprehensive investigation of accelerometer noise will conclude this paper. The noise signal is gathered under various conditions for comparison. Typically, this research illustrates a potential difficulty with microcontroller noise signal reception accuracy. The impact and potential explanation of such a problem on noisy signal reception will also be discussed.
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