摘要
该文提出了一种在线调整权值的多传感器自适应滤波数据融合跟踪算法,用于解决复杂背景下机动目标跟踪问题。首先自适应寻找各个传感器所对应的最优加权因子,确定融合后某一时刻目标最优观测值;其次,以输入信号作为相关自适应滤波器的观测信号,通过新息相关自适应滤波算法根据状态方程及观测方程中误差的变化,实时动态地调整增益矩阵,同时依据自适应滤波状态偏差输出信号及当前观测数据,应用模糊推理在线调整各传感器权值,最终系统输出即为测量轨迹在两级自适应调整融合下最优轨迹。仿真结果证明了算法有效性。
A scheme about multi-sensor data fusion based on adaptive filter is developed for improve tracking precision for moving power-driven target under complicated air-battle environment. At first, optimal weight for sensors are found by measuring data to optimize target point x of anytime. Secondly, the x point is put into adaptive filter as input signal, Plus matrix is adjusted according to change of state noise and observation noise of system at the same time. According to adaptive filter system state noise output and current data, weight for sensors is adjusted on line by using fuzzy logic system. Finally, the output signal is a fusion track that is gained passing through two class self-adapt signal process. The simulation result demonstrates the fusion algorithm is effective,
出处
《电子与信息学报》
EI
CSCD
北大核心
2008年第8期1901-1904,共4页
Journal of Electronics & Information Technology
基金
国家自然科学基金重点项目(60634030)
国家留学基金项目(留金出[2005]3069号)资助课题
关键词
目标跟踪
自适应滤波
数据融合
模糊推理
多传感器
Target tracking
Self-adapt filter
Data fusion
Fuzzy logic inference
Multi-sensor
