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Inertial Sensor Signals Denoising with Wavelet Transform

机译:惯性传感器信号的小波降噪

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摘要

In the current paper we propose a new software procedure for processing data from an inertial navigation system boarded on a moving vehicle, in order to achieve accurate navigation information on the displacement of the vehicle in terms of position, speed, acceleration and direction. We divided our research in three phases. In the first phase of our research, we implemented a real-time evaluation criterion with the intention of achieving real-time data from an accelerometer. It is well-known that most errors in the detection of position, velocity and attitude in inertial navigation occur due to difficult numerical integration of noise. In the second phase, we were interested in achieving a better estimation and compensation of the gyro sensor angular speed measurements. The errors of these sensors occur because of their miniaturization, they cannot be eliminated but can be modelled by applying specific signal processing methods. The objective of both studies was to propose a signal processing algorithm, based on Wavelet filter, along with a criterion for evaluating and updating the optimal decomposition level of Wavelet transform for achieving accurate information from inertial sensors. In the third phase of our work we are suggesting the utility of a new complex algorithm for processing data from an inertial measurement unit, containing both miniaturized accelerometers and gyros, after undergoing a series of numerical simulations and after obtaining accurate information on vehicle displacement
机译:在当前的论文中,我们提出了一种新的软件程序,用于处理搭载在行驶中的车辆上的惯性导航系统中的数据,从而获得有关车辆在位置,速度,加速度和方向方面的位移的准确导航信息。我们将研究分为三个阶段。在研究的第一阶段,我们实施了实时评估标准,旨在从加速度计获得实时数据。众所周知,惯性导航中的位置,速度和姿态检测中的大多数错误是由于噪声的数值积分困难而发生的。在第二阶段,我们对获得更好的陀螺仪传感器角速度测量值的估计和补偿感兴趣。这些传感器的错误是由于它们的小型化而引起的,无法消除它们,但可以通过应用特定的信号处理方法对其进行建模。两项研究的目的都是提出一种基于小波滤波器的信号处理算法,以及评估和更新小波变换的最佳分解水平的准则,以从惯性传感器获得准确的信息。在我们工作的第三阶段,我们建议使用一种新的复杂算法来处理来自惯性测量单元的数据,该惯性测量单元包含微型加速度计和陀螺仪,经过一系列数值模拟并获得了有关车辆排量的准确信息之后

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