无线自组传感器网络定位算法研究
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摘要
近年来,随着无线自组传感器网络的快速发展和广泛应用,无线自组传感器网络定位技术逐渐成为无线传感器网络研究的重要支撑技术之一,具有重大的研究价值。在一些无线传感器网络应用中,如目标识别、监测和跟踪,位置信息成为了这些应用得以实现的必要前提。节点所采集到的数据必须结合其在测量坐标系内的位置信息才有意义。节点通常使用GPS收发器,但考虑到成本和能耗的关系,在无线自组传感器网络里并不适用。定位信息的准确获取对无线自组传感器网络自定位技术的研究具有重要的理论与实际意义。
     本论文的研究重点是目前无需测距的定位算法中应用最为广泛的DV-Hop定位算法和基于测距的定位算法中的RSSI定位算法。首先,针对DV-Hop算法,本文提出了基于几何学的GDV-Hop定位算法。该算法通过几何斜率的方法选取信标节点,在测距计算上选取不同组合的信标节点,采用最小二乘法,得到未知节点的坐标。仿真表明该算法在无需增加额外硬件设备的情况下,定位精度提高了,并且具有良好的适应性和扩展性。
     其次,针对RSSI算法,本文首先从影响无线传感器网络的定位精度的主要因素出发,分析信号传播模型,选择合适的信号模型-对数衰减模型。然后在信标节点的选取上做了改进,选取离未知节点近的信标节点,距离越远,定位影响越大。对测得的距离求平均值,然后运用三角形质心算法,提高了定位的精度。最后对改进的算法进行了仿真,结果表明改进算法在原算法的基础上将定位精度提高了,并且改进算法相对于原算法具有良好的适应性和扩展性。
In recent years, with the rapid development and wide application of wirelesssensor networks, wireless sensor network positioning technology is becoming one ofthe important technologies in wireless sensor networks, and with significant researchvalue. In wireless sensor network applications, such as target identification,monitoring and tracking, location information has become a necessary prerequisite forthese applications.The data which is collected by the nodes can makes sense onlywhen it is combined with location information in the measurement coordinate system.The nodes always with GPS transceiver, but taking the relationship between cost andenergy consumption into account, it is not applicable in a wireless ad hoc sensornetworks. So, obtain the accurate location information is very important in wireless adhoc sensor network self-positioning technology.
     Now,the most widely used localization algorithm are DV-Hop localizationalgorithm and RSSI location algorithm, this thesis is doing some research on thesealgorithm. First of all, for the DV-hop algorithm, proposed GDV-hop positioningalgorithm. Improvements have been made in the beacon node selection and rangingmethod. The simulation results show the new algorithm’s positioning accuracy isimproved and has a good adaptability and scalability.
     Secondly, for the RSSI algorithm, first starting from the main factors of affecting thewireless sensor network positioning accuracy, analysis of signal propagation model, selectthe appropriate signal attenuation model-logarithmic decrement model. And thenmade improvements in the selection of the beacon node. Select the beacon nodewhich is near from the unknown node. The greater the distance, the greater theimpact of positioning.
     For the average measured distance, use the triangle centroid algorithm toimprove the accuracy. Finally, simulate the improved algorithm. The results show thatthe accuracy of the improved algorithm is improved, and the improved algorithm hasgood adaptability and scalability than the original algorithm.
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