基于交互式多模型扩展维特比容积卡尔曼滤波机场场面运动目标跟踪

根据先进场面运动引导控制系统(advanced surface movement guidance and control system,A-SMGCS)的监视要求,提出一种基于交互式多模型扩展维特比算法(interactive multi-model extended viterbi algorithm,IMMEV)与容积卡尔曼滤波(CKF)相结合的目标跟踪算法,以实现机场场面目标的跟踪。根据机场场面运动目标的运动建立相应的运动模型集,采用交互式多模型算法(IMM)实现目标跟踪;模型集中过多的模型会导致运算复杂性增加,且不能真实反映目标的运动,采用扩展维特比(extended viterbi,EV)算法对IMM进行优化,简化模型集;容积卡尔曼滤波器(cubature Kalman filter,CKF)较传统的滤波算法具有更高的滤波精度和稳定性,将其与IMMEV相结合形成IMMEV-CKF跟踪算法。为了验证所提出的IMMEV-CKF对场面运动目标跟踪性能,仿真研究IMMEV-CKF算法、IMM-UKF和当前统计模型对同一目标的跟踪。仿真结果表明,IMMEVCKF在跟踪精度性能方面要优于IMM-UKF和改进后的当前统计模型。因此,IMMEV-CKF更能满足机场场面运动目标跟踪要求。

Maneuvering Target Tracking on Airport Surface Based on IMMEV-CKF Algorithm

According to Advanced Surface Movement Guidance And Control System (A-SMGCS), this paper proposed a target tracking algorithm based on interactive multi-model extended Viterbi algorithm (IMMEV) combined with Cubature Kalman filter (CKF) to achieve airport surface maneuvering target tracking. The paper established the corresponding model sets according to the motion of the airport scene moving target, and used the interactive multi-model algorithm (IMM) to achieve the target tracking. If the model sets include too many models, the computational complexity will increase, and the maneuvering target cannot be truly reflected. The extended Viterbi (EV) algorithm optimized the IMM and simplified the model sets. The Cubature Kalman filter (CKF) had higher accuracy and stability than the traditional filtering algorithm, and it was combined with IMMEV to form IMMEV-CKF algorithm. In order to verify the performance of IMMEV-CKF algorithm proposed in this paper, the IMMEV-CKF, IMM-UKF and current statistical model algorithm were used to track the same target. The simulation results show that IMMEV-CKF is superior to IMM-UKF and the improved current statistical model in tracking accuracy performance. Therefore, the IMMEV-CKF proposed in this paper can better meet the requirements of airport surface maneuvering target tracking.