摘要
对于存在噪声、杂波和漏检等不确定性因素的目标跟踪,多传感器概率假设密度滤波器通过多个传感器获取不同数目的量测,可以实现估计目标状态及其数目。然而,该滤波器的性能受制于新生目标强度的精确度。通过利用不同传感器的量测集迭代计算新生目标强度,提出一种基于自适应新生强度的多传感器多目标跟踪算法,以解决未知新生目标强度跟踪场景下概率假设密度滤波器的跟踪精度。数值结果表明,在均匀新生目标场景下所提算法具有较高的目标状态和数目估计精度。
Under the target tracking of uncertain factors such as noise,clutter and missed detection,the multi-sensor probability hypothesis density filter can estimate the target state and its number by collecting different numbers of measurements through multiple sensors.However,the performance of the filter is limited by the accuracy of the nascent target intensity.By calculating the intensity of nascent targets using measurement sets of different sensors,this paper proposes a multi-sensor multi-target tracking algorithm based on the adaptive nascent intensity to solve the tracking accuracy of the probability hypothesis density filter in tracking scenarios with unknown birth target intensity.Numerical results show that the proposed algorithm has high accuracy of target state and number estimation under the uniform nascent target scenes.
作者
孙志强
SUN Zhiqiang(Shangqiu Vocational and Technical College,Shangqiu,Henan 476000,China)
出处
《山东商业职业技术学院学报》
2023年第2期97-102,共6页
Journal of Shandong Institute of Commerce and Technology
关键词
新生目标强度
多传感器
概率假设密度
状态估计
目标数目
Nascent target intensity
multiple sensors
probability hypothesis density
state estimate
target number
