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Improvements in The Sensitivity Of Mems Based Gyroscope For Military Applications

机译:基于Mems的陀螺仪在军事上的灵敏度提高

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In this paper, we have devised a novel approach for processing the output signal of the micro electro-mechanical systems (MEMS) gyroscopes for the reduction of noise. The main principles on which the model is developed are Allan Variance and Kalman Filtering. The true angular rate signal in all the three directions were directly modeled to obtain an optimal estimate and to develop a self-compensation for the system without the need of any other sensor information, whether in static or dynamic condition. The Allan variance equation was implemented in order to obtain the noise reactivity of gyroscope and to model the noise components. Then, an optimal Kalman filter model was designed and developed to filter-out the noise and provide an ideal or a likely ideal output, which is noise free. A filtering model for a three-dimensional gyroscope is designed, developed and implemented.
机译:在本文中,我们设计了一种新颖的方法来处理微机电系统(MEMS)陀螺仪的输出信号,以降低噪声。建立模型的主要原理是Allan Variance和Kalman滤波。直接对所有三个方向上的真实角速率信号进行建模以获得最佳估计值,并为系统建立自补偿,而无需任何其他传感器信息,无论是在静态还是动态条件下。执行Allan方差方程是为了获得陀螺仪的噪声反应性并建模噪声分量。然后,设计并开发了最佳卡尔曼滤波器模型,以滤除噪声并提供无噪声的理想或可能的理想输出。设计,开发和实现了三维陀螺仪的滤波模型。

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