摘要
在许多实际情况中,目标测量值通常在极坐标或球坐标中得到,而不是在笛卡尔坐标中得到。此时,目标跟踪实际上是非线性的。在众多的军事与非军事领域,机动目标跟踪都是一个非常重要的问题。机动目标跟踪的困难之处在于目标模型的不确定性。针对非线性机动目标跟踪问题,本文提出了一种扩展式当前统计模型机动目标跟踪算法。该算法不需要假定目标的机动加速度模型,而是直接正确地估计出机动目标的当前状态,不存在任何估计滞后与修正问题。最后,给出了算法的仿真分析。
In many practical applications, the position of a target is usually found in polar coordinates or sphere coordinates, not in Cartesian coordinates. Then, we need use a nonlinear method to solve the problem of target tracking in practice. Maneuvering target tracking is always very important in many military and nonmilitary areas. The difficulties of maneuvering target tracking lie in the uncertainty of state model. The paper presents an extended current statistical model for nonlinear maneuvering target. With the algorithm, the current state of maneuvering target can be estimated directly and correctly without assuming the model of maneuvering acceleration. At last, a Monte Carlo simulation is used to analyze the performance of the method.
出处
《电光与控制》
2004年第2期15-17,共3页
Electronics Optics & Control
基金
全国优秀博士论文作者专项基金(No.2000036)
高校骨干教师基金资助项目(No.3240)
关键词
机动目标
当前统计模型
非线性
跟踪
maneuvering target
current statistical model
nonlinearity
tracking