摘要
针对目前高机动目标跟踪的Jerk模型存在计算复杂度高和α-β-γ模型须预先估计过程噪声标准偏差的不足,提出了一种基于Jerk模型的常增益滤波算法:自适应的α-β-γ-δ模型,并从理论上推导出了上述新模型中α、β、γ和δ的计算公式。对一种典型的目标机动形式进行了Monte Carlo仿真,结果表明了新算法对于解决机动目标跟踪问题的有效性,且运算量远远小于Jerk模型算法。
Aiming at the shortcomings of the computational complexity of the Jerk model for highly maneuvering target tracking and the process noise standard deviation of the α-β-γ model must be estimated in advance,a constant gain filtering algorithm is proposed based on the Jerk model which is named as an adaptive α-β-γ-δ model.The computing formulae for α、β、γ and δ are derived theoretically.Finally,the Monte Carlo simulation results to a typical maneuvering movement show the validity of the new algorithm and the far less computational load than Jerk model.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第31期72-74,77,共4页
Computer Engineering and Applications
基金
国家自然科学基金No.60472060,No.60572034
江苏省自然科学基金No.BK2006081
2006年教育部新世纪优秀人才计划项目~~
