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The Autocovariance Least Squares Technique for GPS Interference/Jamming Detection

机译:GPS干扰/干扰检测的自电转主义最小二乘技术

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In this paper, the Autocovariance Least Squares (ALS) technique is proposed for detecting the Global Positioning System (GPS) measurements' interference or jamming. The interference is modeled by a moderate increase in the measurements noise covariance matrix while jamming is modeled by a larger increase in the measurements noise covariance matrix. The method makes use of the dynamics of the system measured by an inertial measurement unit (IMU) and the propagated residual of an ultra-tightly coupled GPS/IMU Extended Kalman filter (EKF) to form a bank of statistics used to estimate the GPS measurement-noise covariance. Simulated scenarios of different levels of noise magnitude are applied and the proposed method is used to estimate the GPS pseudorange noise covariance matrix. Results are presented at the end of the paper to show the accuracy of the proposed algorithm. The algorithm presented in this paper is vital for high-integrity operation of autonomous navigation systems.
机译:在本文中,提出了用于检测全球定位系统(GPS)测量的干扰或干扰的自电转换最小二乘(ALS)技术。通过测量噪声协方差矩阵的温和性增加,在测量噪声协方差矩阵中的较大增加模型时,通过测量噪声协方差矩阵的温和性增加。该方法利用由惯性测量单元(IMU)测量的系统的动态,以及超紧密耦合的GPS / IMU扩展卡尔曼滤波器(EKF)的传播残余,以形成用于估计GPS测量的统计数据 - 不良协方差。应用了不同级别的噪声幅度的模拟场景,并且该方法用于估计GPS伪奇噪声协方差矩阵。结果显示在纸张末尾,以显示所提出的算法的准确性。本文呈现的算法对于自主导航系统的高完整性运行至关重要。

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