摘要
交叉定位的思想可以用来简化数据关联 ,实现状态估计。但在杂波或多目标的环境中 ,定位法会产生大量虚假目标。通过分析传感器数目的选择 ,来限定虚假目标生成的概率。提出了一种基于HMM(HiddenMarkovModel)的全邻似然估计跟踪算法。该算法采用观测 -航迹关联 ,具有相对简单的多项式复杂度。由于传感器量测的融合在状态空间中统一进行 ,该算法可推广到异类传感器组成的系统中。
With the idea of cross-location, data association and state estimation can be realized. But a lot of ghosts will be generated in cluttered or multitarget environment. In order to limit the generation of ghosts, the selection of the number of sensors is analyzed. An all-neighbour likelihood estimation algorithm based on HMM is given. This algorithm can simplify the data association and has polynomial complexity. For the sensor datum is fused in the state space uniformly, so the algorithm can be extended to the dissimilar sensor systems easily.\;
出处
《系统工程与电子技术》
EI
CSCD
2000年第8期52-57,共6页
Systems Engineering and Electronics
基金
国防预研基金资助课题!(5980 1 9)
国家教委博士点基金资助课题!(970 3352 6)
关键词
交叉定位
多传感器
多目标跟踪
算法
Translocation\ \ Multisensor\ \ Multitarget tracking\ \ Algorithm