| 基于不敏Kalman滤波的多传感器数据融合算法 |
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| 引用本文： | 尚晓星,李俊霞. 基于不敏Kalman滤波的多传感器数据融合算法[J]. 河南师范大学学报(自然科学版), 2011, 39(4): 66-69 |
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| 作者姓名： | 尚晓星 李俊霞 |
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| 作者单位： | 1. 焦作师范高等专科学校物理系,河南焦作,454001
2. 河南理工大学计算机科学与技术学院,河南焦作,454000 |
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| 摘 要： | 针对非线性系统状态估计的有效融合问题,给出了一种基于不敏Kalman滤波的多传感器数据融合算法.首先,依据单传感器的量测利用不敏Kalman滤波器得到局部状态估计值；其次,依据模糊集合理论中隶属度的性质构建反映局部状态估计结果的支持度函数和支持度矩阵,进而实现对于各局部状态估计之间蕴含冗余和互补信息的充分提取；最终,通...
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| 关 键 词： | 数据融合 非线性滤波 支持度函数 支持度矩阵 不敏卡尔曼滤波 |
A Novel Multi-sensor Data Fusion Algorithm Based on Unscented Kalman Filter |
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| SHANG Xiao-xing,LI Jun-xia. A Novel Multi-sensor Data Fusion Algorithm Based on Unscented Kalman Filter[J]. Journal of Henan Normal University(Natural Science), 2011, 39(4): 66-69 |
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| Authors: | SHANG Xiao-xing LI Jun-xia |
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| Affiliation: | SHANG Xiao-xing1,LI Jun-xia1,2(1.Physics and Electronic Engineering Department,Jiaozuo Teacher's College,Jiaozuo 454001,China,(2.School of Computer Science and Technology,Henan Polytechnic University,Jiaozuo 454000,China) |
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| Abstract: | For the effective fusion of nonlinear system state estimation,a novel multi-sensor data fusion algorithm based on unscented Kalman filter is given.Firstly,unscented Kalman filter is used to estimate local state estimation value of nonlinear system by single sensor measurement data.Then,according to the principle of the membership degree in fuzzy set theory,support degree function and support degree matrix are constructed,so that the complementary and redundancy information among local state estimation value... |
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| Keywords: | data fusion non-linear filter support degree function support degree matrix unscented Kalman filter |
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