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A new incremental Kalman filter under poor observation condition

机译:不良观测条件下的新型增量式卡尔曼滤波器

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The unverified or uncorrected observation equation of system usually leads to unknown system errors and filtering errors. In this paper, a new incremental Kalman filtering algorithm is presented, which can eliminate the unknown system errors and improve the accuracy of state estimators. This algorithm is simple in form and easy to be applied in engineering practice. The simulation results show its effectiveness and feasibility.
机译:未经验证或未经校正的系统观测方程通常会导致未知的系统误差和滤波误差。本文提出了一种新的增量式卡尔曼滤波算法,可以消除未知的系统误差,提高状态估计器的精度。该算法形式简单,易于在工程实践中应用。仿真结果表明了该方法的有效性和可行性。

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