According to the noise contained in many sensor data, an algorithm based on support degree and adaptive weighted spatial-temporal fusion of the multi-sensor is proposed.
针对多传感器测量数据中含有的噪声，提出一种基于多传感器支持度和自适应加权时空融合算法。
The principle and shortage of traditional weighted average algorithm is analyzed in this paper, and then a new image fusion algorithm based on enhancement on sensitive areas zone is proposed.
论文分析了传统的加权平均算法融合的原理和不足，并在此基础上提出了基于特征区域增强的融合算法，在一定程度上改善了融合图像的质量。
A new multi-sensor optimal information fusion algorithm weighted by scalars is presented in the linear minimum variance sense.
提出了一种新的标量加权线性最小方差意义下的多传感器最优信息融合算法。
With these numerical integration methods as mathematics tools, the new tracking algorithm, non-linear estimators weighted fusion filter, is developed, we call it TNF.
以这些数值积分方法为数学工具，推导出了非线性估计子加权融合滤波器，本文中简称TNF。
With these numerical integration methods as mathematics tools, the new tracking algorithm, non-linear estimators weighted fusion filter, is developed, we call it TNF.
以这些数值积分方法为数学工具，推导出了非线性估计子加权融合滤波器，本文中简称TNF。
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