论文标题
移动无线网络中化学传感器的校准
Calibration of chemical sensors in mobile wireless networks
论文作者
论文摘要
部署在移动平台上的低功率化学传感器使得可以监测大型城市地区的污染物浓度。但是，化学传感器容易漂移（例如，衰老，损害，中毒），必须定期校准。在本文中，我们提出了一种机会主义的校准方法，该方法依赖于传感器之间的相遇。在彼此附近时，传感器交换测量并使用累积信息重新校准。我们将校准过程作为加权最小二乘，其中最新的测量值分配了最高的权重。我们使用指数衰减功能（时间）对重量进行建模，并使用模拟退火（SA）优化衰减常数。我们在模拟传感器网络上验证了所提出的方法，该方法具有由随机通道（RWP）模型驱动的传感器的迁移率。我们以不同权重函数和网络大小的平均校准误差为角度提出结果。
Low-power chemical sensors deployed on mobile platforms make it possible to monitor pollutant concentrations across large urban areas. However, chemical sensors are prone to drift (e.g., aging, damage, poisoning) and have to be calibrated periodically. In this paper, we present an opportunistic calibration approach that relies on encounters between sensors; when in vicinity of each other, sensors exchange measurements and use the accumulated information to re-calibrate. We formulate the calibration process as weighted least-squares, where the most recent measurements are assigned the highest weights. We model the weights with an exponential decay function (in time) and optimize the decay constant using simulated annealing (SA). We validated the proposed method on a simulated sensor network with the sensors' mobility driven by random-waypoint (RWP) models. We present results in terms of average calibration errors for different weight functions, and network sizes.
