基于激光传感技术的目标跟踪

Target tracking based on laser sensor

为了提高目标跟踪的准确性和实时性,针对当前算法跟踪误差大的缺陷,结合均值漂移算法和卡尔曼滤波的优点,提出了传感器节点的视频目标跟踪算法。首先对卡尔曼滤波器相关参数进行优化,并确定其初始状态变量,然后采用均值漂移算法估计候选目标与模板目标之间相似度,实现目标自适应跟踪,最后采用仿真实验测试算法的跟踪性能。结果表明,该方法可以实现目标准确跟踪,提高了目标跟踪的精度,而且实时性要优于对比算法,具有更广的应用范围。

In order to improve the accuracy and the real-time ability of target tracking, in view of the current error defects, combined with the advantages of mean shift algorithm and Caiman filter, this paper proposes a new video target tracking of wireless sensor networks based on sensor nodes. Firstly, optimize Caiman filter relative parameters and determine its initial state variables. Then use mean shift algorithm to estimate the similarity between candidate object and target template to realize adaptive target localization and tracking. Finally use simulation to test tracking performance of the algorithm. The results show that this method can achieve accurate tracking of targets, improve the accuracy of target tracking, and the real-time performance is better than the contrast algorithm, which has a wider use of applications.