As a research hotspot in Visual Sensor Networks (VSNs) , k-coverage problem has aroused general attention of many researchers . Aiming at the problem of moving targets k-coverage problem in visual sensor networks , we propose a new target coverage probability evaluation model for non-uniform motion ,which consider all the possible locations of every target at the next moment and the motion behavior of non-uniform motion objects by using probabilistic prediction theory . This method can increase the probability of k-coverage . A new predictive distributed k-covering optimization algorithm is proposed . Sensor nodes exchange coverage information and make decisions in communication range .Finally ,through a series of simulation experiments ,the experimental results verify the effectiveness and feasibility of the algorithm and model .%k覆盖问题作为视频传感器网络中的一个研究热点,引起了许多研究者的关注.针对视频传感器网络中的移动目标k级覆盖问题,结合概率预测思想,充分考虑非匀速移动目标的运动特性和下一时刻目标有可能达到的位置,建立了一种移动目标覆盖概率评估模型,提高了k覆盖的概率.同时,提出了新的基于预测的分布式k覆盖优化算法,传感器节点在通信范围内交换覆盖信息并进行决策.最后通过一系列仿真实验,实验结果验证了该算法和模型的有效性和可行性.
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