gusucode.com > 基于RSSI测距室内定位改进质心算法 > 基于RSSI测距室内定位改进质心算法\文件说明.txt

    室内定位技术具有巨大的市场需求,但由于室内定位受到噪声、多径反射、温度、环境、阴影衰落等因素影响,其定位精度显著地降低。为了提高室内节点的定位精度,针对传统的质心定位算法精确度低的问题,提出了基于RSSI节点测距的改进质心定位算法。该算法对锚节点接收到的RSSI数据进行拟合以此能够在BP神经网络基础上确定损耗模型参数值,采用改进的质心定位算法进行定位,并在原有的三点定位的基础上,通过节点之间的数学转换,将三点定位法改进为六点质心定位算法。为验证所提算法的有效性和可行性,基于Matlab仿真平台进行了仿真实验。仿真实验结果表明,相对于传统的质心定位算法,所提出的算法显著地提高了室内定位的精度。 Indoor positioning technology has a huge market demand, but because of indoor positioning by noise, multipath reflection, temperature, environment, shadow fading and other factors, the positioning accuracy significantly reduced. In order to improve the positioning accuracy of indoor nodes, an improved centroid localization algorithm based on RSSI node distance is proposed for the problem of low precision of traditional centroid localization algorithm. The algorithm can fit the RSSI data received by the anchor node so that the value of the loss model can be determined on the basis of BP neural network, and the improved centroid localization algorithm is used to locate the RSSI data. Based on the original three-point positioning, Between the mathematical transformation, the three-point positioning method to improve the six-point centroid localization algorithm. In order to verify the validity and feasibility of the proposed algorithm, the simulation experiment is carried out based on Matlab simulation platform. The simulation results show that compared with the traditional centroid localization algorithm, the proposed algorithm can improve the accuracy of indoor positioning.