摘要
将强跟踪滤波理论与多传感器数据融合估计方法相结合 ,提出基于强跟踪滤波器的多传感器数据融合估计新算法。对拥有相同采样率的分布式多传感器单模型非线性动态系统 ,应用强跟踪滤波器 ,得到目标状态基于全局信息融合估计结果 ,并利用计算机仿真结果对算法的有效性进行了验证。这些工作初步解决了Kalman滤波中由于模型的不确定性而造成估计误差值偏大情况下的状态融合估计问题 。
By combining the strong tracking filtering theory with data fusion estimation approaches, we put forward a new fusion estimation algorithm of multi sensor based on strong tracking filter. For the multi sensor and single model nonlinear dynamic systems with the same sample rates for every sensor, we can obtain the optimal fusion estimate on the basis of global information by use of strong tracking filter, and illustrate the effectiveness of the new algorithm by way of an example, which give a primary solution to the fusion estimation problem of having bigger errors produced by Kalman filter because of uncertainties of modeling system. The work enriches and develops the information fusion theory.
出处
《上海海运学院学报》
北大核心
2001年第3期162-166,共5页
Journal of Shanghai Maritime University
