N-P准则下的多传感器信息融合算法设计
Multi-Sensor Information Fusion Algorithm Design under N-P Criterion
荀亚敏 1张杰 1翟芸翎 1翟灵瑞1
作者信息
- 1. 潍柴动力股份有限公司,山东 潍坊 261061
- 折叠
摘要
传感器是环境感知中实现高度自动化的关键组件.为了实现多传感器系统高水平的抗干扰性和鲁棒性,针对局部传感器稳定性差及精度不足的问题,创新性地提出了一种基于统计判决的多传感器信息融合算法.首先,完成了多传感器融合的基本建模,并设计了单传感器的单值概率特性计算方法.然后,对传统单传感中卡尔曼滤波方法进行了优化设计,消除了累计误差的影响.最后,通过引入奈曼-皮尔逊(N-P)准则完成了多维度评估的多传感器信息融合算法设计.接收者操作特征(ROC)曲线评估试验结果证明了所提算法在理论上的正确性和合理性.相比其他算法,所提算法在抗干扰性和容错性等性能方面有显著优势.实际无人机测试证明了该算法具有一定的实用性.
Abstract
Sensors are the key components for realizing a high degree of automation in environmental sensing.To realize a high level of anti-interference and robustness of multi-sensor systems,a multi-sensor information fusion algorithm based on statistical judgment is innovatively proposed to address the problems of poor stability and insufficient accuracy of local sensors.Firstly,the basic modeling of multi-sensor fusion is completed,and the calculation method of single-value probability characteristics of single sensors is designed.Then,the Kalman filtering method in traditional single sensing is optimally designed and the effect of cumulative error is eliminated.Finally,the design of multi-sensor information fusion algorithm for multi-dimensional evaluation is accomplished by introducing the Neyman-Pearson(N-P)criterion.The receiver operating characteristic(ROC)curve evaluation test proves the theoretical correctness and rationality of the proposed algorithm.Compared with other algorithms,the proposed algorithm has significant advantages in the performance of anti-interference and fault tolerance.The actual unmanned aerial vehicle test proves that the algorithm has some practicality.
关键词
多传感器融合/信息融合/统计判决/卡尔曼滤波/奈曼-皮尔逊准则/接收者操作特征曲线Key words
Multi-sensor fusion/Information fusion/Statistical judgment/Kalman filtering/Neymen-Pearson(NP)criterion/Receiver operating characteristic(ROC)curve引用本文复制引用
出版年
2024
NETL
NSTL
万方数据