基于信息质量选择的动态航迹融合算法

Dynamic Track Fusion Algorithm Based on Information Quality Selection

传统的航迹融合算法未充分考虑传感器精度和量测丢失对航迹质量的影响,从而导致融合后的航迹质量下降。为了提高跟踪性能,提出一种基于信息质量选择的动态航迹融合算法。该算法通过交互式多模型补偿滤波来获得局部航迹和信息熵,然后利用信息熵来度量局部航迹质量。根据设置的双门限筛选出质量好的局部航迹,并将其信息熵归一化的结果赋给传感器的权值,实现权值的动态分配。仿真结果表明,在考虑不同的传感器精度和量测丢失率的情况下,该算法对机动目标的跟踪性能优于已知的航迹融合算法。

The traditional track fusion algorithm does not fully consider the situation that the accuracy of sensors and the measurement loss lead to the track quality degradation.In order to improve the performance of dynamic tracking,a dynamic track fusion algorithm based on information quality selection is proposed.The algorithm obtains the local track and information entropy by interacting multiple model compensation filtering,and then uses the information entropy to measure the quality of the local track.The local track with good quality is selected according to the double threshold.Then,the information entropy normalization result is assigned to the weight of the sensor to realize the dynamic matching of the weight.The simulation results show that the algorithm outperforms the known track fusion algorithm in tracking maneuvering targets with different sensor accuracy and measurement losses.