一种无线传感器信号衰减自适应测距模型

An adaptive ranging model based on energy distance loss of wireless sensors

使用无线传感器作为路标实现机器人定位具有许多优势,但无线传感器与机器人之间的距离测量存在易受环境干扰的缺点.为了解决这一难题,在对无线传感器射频信号衰减原理分析的基础上,基于在线学习的方法为无线传感器路标建立自适应的信号衰减测距模型.由于模型学习过程是在线进行的,环境因素对无线信号传播衰减的影响被包含在模型中,故此测距模型提高了对无线信号传播环境的适应能力.此外,把路标的身份作为测距模型的输入,从而区分了传感器个体的差异,实验结果证明了这种建模方法在提高无线传感器测距精度方面的有效性.

Using wireless sensors as landmarks for mobile robot localization has many advantages,but the process of measuring the distance between the robot and wireless sensor is susceptible to environmental disturbance.To solve this difficult problem,the radio frequency signal decay theory was analyzed,and an adaptive signal decay range model was established for wireless landmarks based on the online learning method.The model learning was completed online,so the effect of the environmental factors on the decay of wireless signal transmission was included in the online modeling process;correspondingly,the adaptive ability of the model was improved.In addition,the identity numbers of different wireless landmarks were also input into the artificial neural network model so that differences among certain sensors were considered.Experiments show that the proposed modeling method is effective for improving wireless sensor ranging precision.