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Adaptive fusion algorithms based on weighted least square method

机译:基于加权最小二乘法的自适应融合算法

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摘要

Weighted fusion algorithms, which can be applied in the area of multi-sensor data fusion, are advanced based on weighted least square method. A weighted fusion algorithm, in which the relationship between weight coefficients and measurement noise is established, is proposed by giving attention to the correlation of measurement noise. Then a simplified weighted fusion algorithm is deduced on the assumption that measurement noise is uncorrelated. In addition, an algorithm, which can adjust the weight coefficients in the simplified algorithm by making estimations of measurement noise from measurements, is presented. It is proved by emulation and experiment that the precision performance of the multi-sensor system based on these algorithms is better than that of the multi-sensor system based on other algorithms.
机译:基于加权最小二乘法,提出了可应用于多传感器数据融合领域的加权融合算法。通过关注测量噪声的相关性,提出了建立加权系数与测量噪声之间关系的加权融合算法。然后,在测量噪声不相关的假设下,推导了简化的加权融合算法。此外,提出了一种算法,该算法可以通过根据测量结果估算测量噪声来调整简化算法中的权重系数。通过仿真和实验证明,基于这些算法的多传感器系统的精度性能要优于基于其他算法的多传感器系统。

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