An event-triggered distributed positioning method of a heterogeneous WSN
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摘要: 由于电磁波传输的多径效应和信号干扰，基于接收信号强度（RSS）测距的室内定位精度较低，本文提出一种融合RSS和惯性测量的异构无线传感器网络(WSN)室内定位方案，它是采用基于位置估计信任度的分布式一致性容积信息滤波算法来协同估计目标的位置。引入事件触发机制，基于RSS信号强度触发WSN节点唤醒，以提高网络的抗干扰性和降低网络能耗。室内移动小车的定位仿真和实验测试结果表明，所提出的WSN融合定位精度明显优于单一定位方法，具有显著的抗干扰性能，且分布式定位和事件触发机制可有效地降低网络能耗。Abstract: Due to multi-path effect and electromagnetic interference, RSS-based indoor positioning systems has lower accuracy. Aiming at this shortcoming, this paper proposes an indoor positioning scheme of a heterogeneous wireless sensor network (WSN) by integrating the RSS and inertial measurement. The distributed consensus cubature information filters with credibility evaluation is utilized to estimate target positions collaboratively. An event triggering mechanism is introduced to awaken the sensor nodes when the strength of RSS signals are satisfied for improving the network anti-interference and reduce network energy consumption. It is shown from the simulation and experiment results via mobile cars that the proposed method has higher positioning accuracy than and a single positioning method, and remarkable anti-interference performance. Moreover, the distributed positioning scheme and event-triggering mechanism can effectively reduce network energy consumption.
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图 2 异构WSN定位系统的多传感器多层级融合体系
Figure 2. Multi-sensor multi-level fusion system for heterogeneous WSN positioning system
图 6 事件触发机制对定位误差的影响
Figure 6. Influence of event triggering mechanism on positioning error
RMSE—Root Mean Square Error
图 9 实验室RSS功率与距离模型拟合数据
Figure 9. Fitting data of RSS power and distance model in laboratory
图 12 定位结果及各轨迹段服务节点示意
Figure 12. positioning result and service node indication of each track segment
表 1 算法在各种电磁干扰环境下的定位误差
Table 1. Positioning error of the algorithm in various electromagnetic interference environments
MAE/m RMSE/m Average Maximum Average Maximum DC interference 0.264 0.917 0.270 0.935 AC interference 0.250 0.902 0.253 0.912 Random noise
interference0.298 1.076 0.315 1.104 
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