摘要
为提高非高斯噪声条件下机动目标跟踪的精度,提出基于交互式多模型极限迭代无偏有限脉冲响应滤波(IMM-极限迭代UFIR)算法。采用对噪声统计特性不敏感的极限迭代无偏有限脉冲响应滤波(UFIR)作为其子滤波器,对各模型进行状态估计,最后通过对各模型的输出结果综合得到机动目标状态。仿真结果表明,在噪声条件复杂的情况下,该算法比交互式多模型卡尔曼滤波(IMM-KF)具有更高的跟踪精度和稳定性,计算量小于IMM-PF,算法能较好地兼顾跟踪精度和计算量两方面性能。
To improve the precision of maneuvering target tracking under non-Guassian noise condition,a tracking algorithm based on Interactive Multi-Model ultimate iterative Unbiased Finite Impulse Response（ IMM-ultimate iterative UFIR） filter is proposed. The algorithm takes the ultimate iterative UFIR,which has lower sensitivity to errors in the noise statistics,as its sub-filter to estimate the state of each model,and the state of maneuvering target is obtained by fusing the states of multiple models. Simulation results show that：under complex noise conditions,IMM-iterative UFIR has a higher precision than that of the Interactive Multiple Model Kalman Filter（ IMM-KF）,and less calculation cost than that of IMM-PF,which has a good balancing between the tracking precision and calculation amount.
作者
武青海
曲朝阳
WU Qing-hai;QU Zhao-yang(School of Electrical and Information Engineering, Jilin Agricultural Science and Technology University, Jilin 132101, China;School of Information Engineering, Northeast Dianli University, Jilin 132012, China)
出处
《电光与控制》
北大核心
2018年第6期35-38,51,共5页
Electronics Optics & Control
基金
吉林省科技发展计划项目(20180623004TC)
关键词
机动目标
目标跟踪
交互式多模型
极限迭代UFIR
状态估计
maneuvering target
target tracking
interactive multi-model
ultimate iterative UFIR
state estimation
