模糊数据融合在目标跟踪中的应用

在目标跟踪滤波算法的基础上，提出利用模糊理论进行数据融合的算法。应用模糊理论，对双传感器的滤波数据进行特征提取，并在一定的隶属函数和模糊规则下对其进行模糊推理，得到随目标机动情况自动调节加速度方差的系数调节值，使之保持对目标机动的快速响应。分析中采用蒙特卡洛仿真方法，对融合前后的滤波结果进行比较。模糊数据融合利用领域专家总结的相关知识，将融合结果反馈给单传器，以提高各单传感器的跟踪精度。

The Application of Fuzzy Data Fusion in Targets Tracking

On the basis of the filtering algorithm of target tracking, the data fusion algorithm adopting fuzzy theory was proposed. By use of fuzzy theories, the feature extraction was made for the filter data from two sensors and then the fuzzy illation was done under certain subordinate functions and rules, thereby a coefficient was got to adjust the acceleration square variance automatically in order to keep the rapid response to the practical conditions, in addition, the Monte Carlo simulation methods were used to compare the results obtained before and after the data fusion algorithm was applied. The fuzzy algorithm fully makes use of the relative knowledge extracted from the experts in the field, the feedback of the fusion results to the single sensor can enhance the single sensor's precision.