基于渐消因子的双机协同机动目标定位

摘要

In traditional two cooperative aircraft networking localization models,Interacting Multiple Model algorithm (IMM) is widely used. However,IMM depends on transcendental target maneuvering models,and the model number can hardly meet tracking accuracy and algorithm complexity requirements at the same time in practice. Therefore,the fading factor is introduced here to real-time adaptively correct maneuvering target state estimation deviations,reducing the impact of target movement transcendental model on filtering results and improving the system capability of handling maneuvering targets and the model engineering applicability.%传统的双机协同组网目标定位模型中，滤波方法大多为交互式多模型算法。交互式多模型算法的缺陷为需要目标机动先验模型，且模型个数的选择难以同时满足工程上关于跟踪精度和算法复杂性的要求。通过引入渐消因子，实时自适应校正机动目标的状态估计偏差，有效降低了目标运动先验模型对滤波的影响，提高了系统的机动处理能力和模型的工程实用性。