含时间参量的传感器网络修正感知模型  

Improving Sensing Model in Sensor Networks with Temporal Parameter

作　　者：邓瀚林[1] 黄河清[1] 吴明娟[1] 刘海涛[1] 

机构地区：[1]中国科学院上海微系统与信息技术研究所无线传感网与通信重点实验室,上海200050

出　　处：《计算机工程》2010年第22期7-9,共3页Computer Engineering

基　　金：国家科技重大专项基金资助项目(2009ZX03006-007)

摘　　要：目标与传感器之间的距离对传感器感知能力具有重要影响,但现有研究仅考虑以距离作为参量建立量化传感器感知能力的模型,而忽略了时间因素的影响。为此,引入时间参量建立修正的传感器感知模型。实验结果表明,与已有的感知模型相比,该模型能更真实地模拟传感器对目标的感知行为,量化传感器对运动目标的感知能力。The distance between the target and the sensor has significant impact on the sensor＇s sensing capacity. Recent study chooses distance as an important parameter to build sensing model, but ignores that sensor needs time to sense the target and process data. Aiming at this problem, this paper proposes an improved sensing model with temporal parameter. Compared with existing models, the model can capture the behavior of sensors more realistically meanwhile measuring the capacity of sensing moving target.

关 键 词：传感器网络 感知模型 时间参量 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]