机场三维态势呈现中IMMKF平滑ADS-B数据

Smooth ADS-B data by IMMKF for 3D display of airport situation

针对基于广播式自动相关监视(automatic dependent surveillance-broadcast,ADS-B)数据进行机场三维态势呈现的应用,研究了在态势显示的第一步,ADS-B数据精度不高、不平滑问题,预处理后数据可以用于后续插值生成高帧率的航迹数据。交互式多模型卡尔曼滤波(interacting multiple model Kalman filter,IMMKF)算法可以较好地解决机场场面运动目标ADS-B轨迹数据的实时平滑问题。首先,根据飞机的真实运动情况建立了飞机的匀加速运动、匀速转弯运动及匀速运动模型,然后利用卡尔曼滤波Singer模型与IMM相结合的IMMKF算法对场面飞机的ADS-B轨迹进行了跟踪滤波,达到目标轨迹光滑的效果。实验结果表明,与多种经典的滤波方法相比,IMMKF方法在保证了光滑性的情况下跟踪失败概率低,可实时计算,精度能满足要求。

In order to realize the 3D situation display of airport based on the automatic dependent surveil-lance-broadcast（ADS-B）data,its smoothing method is developed in the first step of airport 3D display.The ADS-B data must be pretreated because it is unsmooth with low accuracy for 3D display of the moving aircraft on airport surface.After smooth pretreatment,ADS-B data can be interpolated to high-frequency track data which is used for 3D display.So the interacting multiple model Kalman filter（IMMKF）algorithm is used to smooth the track.First,according to the actual movement of aircraft,three motion models with respect to con-stant acceleration,constant turn and constant velocity are constructed separately.Second,the IMMKF algo-rithm which combines IMM and Kalman Singer filter is used to track and smooth ADS-B data.Compared with other several classical filters,the experiment results indicate that this method achieves the lower failure proba-bility of tracking with enough smoothness,realtime calculation and high accuracy.