计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 211000165-6.doi: 10.11896/jsjkx.211000165
杨思星1,2, 李宁1, 郭艳1, 杨延宇2
YANG Si-xing1,2, LI Ning1, GUO Yan1, YANG Yan-yu2
摘要: 随着人工智能技术的发展,智能干扰源可通过改变自身发射功率来提高干扰效果,导致传统基于接收信号强度的定位技术失效。为此,引入传感器唤醒机制,研究基于块压缩感知的多干扰源定位方法。首先,周期性地唤醒传感器节点,同时提高传感器节点利用有效性和定位信息采集精确性;其次,考虑到在干扰源发射功率未知且变化的情况下无法确定距离与接收信号强度之间的关系,引入参考功率对智能变化的干扰源功率进行处理;然后,基于压缩感知理论,将定位问题建模为块稀疏向量重构问题;最后,通过探索功率变化规律设计出一种基于变分贝叶斯均值-期望的Wake-VBEM重构算法,精确重构目标位置向量。仿真证明,所提方法在干扰源功率未知且变化时,可同时实现多干扰源位置估计并有效提高网络使用寿命。
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