摘要
多传感器目标跟踪系统中,各传感器量测周期的不同导致局部量测或估计到达融合中心的时间不同步。使用航迹融合和卡尔曼滤波方法,各局部传感器在共享融合中心数据的基础上进行独立滤波估计,融合中心根据各局部航迹插值对准进行融合,提出了一种适合于任意多传感器速率构成的异步环境跟踪的方法。实验仿真结果表明,该方法能够很好地完成异步环境的目标跟踪任务,跟踪效果明显好于各局部传感器。
Owning to different measurement rates, measurements or local estimates arrive at fusion center asynchronously in most multi-sensor tracking systems. Combining track-level fusion and kalman filter, an asynchronous tracking algorithm was proposed in this paper. In the algorithm, local sensor takes the estimate independently on basis of sharing data from fusion cen- ter, and fusion center fusion estimates from local sensors by interpolation and carlibration. We provide an extensive set of ex- perimental evidences with a comparative performance analysis with tracking methods representative of the principal approaches. Results show that the method proposed is effective in asynchronous tracking and the accuracy of center is obviously better than local estimates.
出处
《重庆师范大学学报（自然科学版）》
CAS
北大核心
2012年第6期54-58,共5页
Journal of Chongqing Normal University:Natural Science
基金
重庆市教委科学技术研究项目(No.KJ110805)
重庆理工大学青年基金计划项目(No.2011ZQ9)
重庆理工大学科研启动项目(No.03-60-30)
关键词
多传感器
异步环境
反馈机制
目标跟踪
信息融合
multi-sensor
asynchronous environment
feedback mechanism
object tracking
information fusion
