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Design and Evaluation of a Micro-Electromechanical Systems Inertial Navigation System for Underwater Vehicle

机译:水下航行器微机电系统惯性导航系统的设计与评估

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摘要

The development and evaluation of micro-electromechanical systems inertial navigation system (MEMS-INS) for the navigation of underwater vehicles, both autonomous underwater vehicles (AUVs) and remotely-operated vehicles (ROVs), is extremely challenging. The navigation estimation of underwater vehicles is easily influenced by error noise arising in the micro inertial sensors. Therefore, this paper presents a hybrid calibration method to build the MEMS-INS and to overcome the challenges of micro inertial sensors for underwater navigation. The MEMS-INS is composed of a micro-accelerometer, a micro-gyroscope, and signal processing circuits. In general, the sources of error noise can be categorized into two groups, deterministic and stochastic: the former primarily include bias errors, misalignment and nonlinearity; the latter include temperature effects and signal drifting. Linearity calibration is used to modify deterministic errors and wavelet analysis can suppress stochastic noise. The hybrid calibration method therefore includes bias compensation, linearity calibration and wavelet signal processing to enhance the accuracy and performance of the MEMS-INS. The experimental results demonstrate that the output signal can be corrected suitably by means of the proposed method. Overall, the results confirm the strong potential of micro inertial sensors for use in underwater vehicle navigation applications.
机译:用于水下航行器的微机电系统惯性导航系统(MEMS-INS)的开发和评估非常困难,无论是水下航行器(AUV)还是远程航行器(ROV)。水下航行器的导航估计很容易受到微惯性传感器中产生的误差噪声的影响。因此,本文提出了一种混合校准方法,以构建MEMS-INS并克服用于水下导航的微惯性传感器的挑战。 MEMS-INS由微加速度计,微陀螺仪和信号处理电路组成。通常,误差噪声的来源可分为确定性和随机性两类:前者主要包括偏置误差,失准和非线性。后者包括温度影响和信号漂移。线性校准用于修正确定性误差,小波分析可以抑制随机噪声。因此,混合校准方法包括偏置补偿,线性校准和小波信号处理,以增强MEMS-INS的准确性和性能。实验结果表明,该方法可以对输出信号进行适当的校正。总体而言,结果证实了用于水下车辆导航应用的微惯性传感器的强大潜力。

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