摘要
目标跟踪领域的一个研究重点是如何解决在密集杂波环境下机动目标的跟踪问题。机动目标跟踪的关键是解决目标模型的不确定性,而密集杂波环境则使这个问题变得更加复杂。针对这一问题,提出一种当前模型概率数据互联算法。该算法将当前模型算法与概率数据互联相结合,在使用概率数据互联算法的同时,利用当前模型算法对目标出现的机动进行自适应滤波。最后,给出了算法的仿真分析,仿真结果说明该方法能够有效地跟踪杂波环境中的机动目标。
How to track a maneuvering target is a key problem of target tracking in clutter. The difficulties of the maneuvering target tracking lies in the uncertainty of state model, and the clutter make it more complex. The paper presents a current statistical probabilistic data association algorithm for tracking a maneuvering target in clutter. The algorithm combines current statistical algorithm with probabilistic data association algorithm. When this algorithm estimate the state of a maneuvering target with current statistical algorithm, the probabilistic data association algorithm is used to resolve association problem. At last, a Monte Carlo simulation is used to analyze the performance of the method. And the results suggests this algorithm can estimate a maneuvering target in clutter efficiently.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2005年第1期4-7,共4页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金资助项目(60172033)
全国优秀博士论文作者专项基金项目(200036)
高校骨干教师基金资助项目(3240)
关键词
机动目标
当前统计模型
概率数据互联
跟踪
maneuvering target
current statistical model
probabilistic data association
tracking
