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Applied research of location fingerprint positioning system based on the improved AUKF algorithm

机译:基于改进AukF算法的位置指纹定位系统应用研究

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Because of the signal error existing in mine personnel positioning when using location fingerprint positioning, the paper proposes self-adaptive unscented Kalman filter (Adaptive UKF, AUKF) algorithm. The filtering algorithm can actively suppress signal diverging and compensate for the signal loss brought about by the noise, and further improve the accuracy of the sample signal in location fingerprint positioning method. By associating the accurate signal positioning with the position algorithm, the system can obtain more accurate target location.
机译:由于矿井人员在使用位置指纹定位时存在的信号误差,该论文提出了自适应Uncented Kalman滤波器(自适应UKF,AukF)算法。滤波算法可以主动抑制信号发散并补偿由噪声引起的信号损失,并进一步提高了位置指纹定位方法中的样本信号的精度。通过将准确的信号定位与位置算法相关联,系统可以获得更准确的目标位置。

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