基于自适应容积卡尔曼滤波的交互多模型算法

Interactive Multi-model Algorithm Based on Adaptive Volume Kalman Filter

ADS-B航迹处理主要包括航迹数据滤波和滤波后数据可靠性的判断。飞机飞行运动复杂,而报文需要在飞行过程中向外界发送,此时报文会受到来自外界的影响和干扰,从而使航迹信息出现误差或丢失。为提高ADS-B航迹报文的准确性,文章采用了交互多模型滤波算法,将自适应容积卡尔曼滤波器作为交互多模型滤波算法的滤波器,并将当前统计模型作为交互多模型的子模型。仿真结果表明,论文改进的算法提高了滤波算法的滤波性能,相较于传统的交互多模型滤波算法具有更高的滤波精度。

ADS-B track processing mainly includes track data filtering and judgment of data reliability after filtering.The flight motion of the aircraft is complex,and the message needs to be sent to the outside world during the flight.At this time,the message will be affected and disturbed by the outside world,resulting in the error or loss of track information.In order to improve the accuracy of ADS-B track message,the interactive multi-model filtering algorithm is adopted,and the adaptive volume Kalman filter is used as the filter of interactive multi-model filtering algorithm.The current statistical model is regarded as a submodel of the interactive multi-model.The simulation results show that the improved algorithm improves the filtering performance of the filtering algorithm,and has higher filtering accuracy than the traditional interactive multi-model filtering algorithm.