基于最速下降法的室内定位技术研究
Research on Steepest Descent Method Based Indoor Location Estimation Technology
DOI: 10.12677/OE.2017.71005, PDF, HTML, XML, 下载: 1,810  浏览: 4,048 
作者: 黄海波*：南京邮电大学通达学院，江苏 扬州；周蓉, 王文锐, 宋伟, 田龙斌：南京邮电大学，江苏 南京
关键词: RSSI；室内定位；对数正态阴影衰落模型；三边定位算法；最速下降法；RSSI； Indoor Positioning； Log-Normal Shadow Fading Modal； Trilateral Localization Algorithm； Steepest Descent Method
摘要: 室内定位技术解决了卫星信号到达地面时较弱，不能穿透建筑物的问题。传统的室内定位技术由于RSSI受限于多径效应和时间波动性，定位时有很大的不稳定性。针对WSN室内定位的关键性问题的研究，本文提出了一种基于RSSI的WSN的最速下降的定位算法。该方法通过三个接入点即参考节点来求出待测节点的坐标，结合了对数正态阴影衰落模型、三边定位算法以及最速下降法。本文先采用对数正态阴影衰落模型得出待测节点相对于各个参考节点的距离值；然后用三边定位算法求出定位节点的估计坐标；最后用最优化方法对估计的坐标值进行优化。仿真结果表明，相对于基于RSSI的传统定位方法，基于最速下降法的室内定位技术具有更高的定位精度。
Abstract: Indoor positioning technology solves the problems that the satellite signal is weak when it reaches the ground and the signal cannot penetrate the structure. Due to the RSSI being limited by multipath effect and the volatility of time, the traditional indoor positioning technology is unstable when positioning. Aiming at the key issues of research in indoor positioning of WSN, a method based on RSSI positioning of the steepest descent algorithm WSN is proposed in the paper. The method uses three access points, namely the reference node, to find the coordinates of the nodes. In addition, the method combines log-normal shadow fading model, trilateral localization algorithm and steepest descent method. Firstly, using the log-normal shadow fading model the value of RSSI has been gotten from the node under test to the reference signal; besides, the trilateral localization algorithm is used to estimate the locating node coordinates; finally, the estimated coordinates are optimized by the optimization method. The simulation results show that, compared with the traditional positioning method based on RSSI, the indoor positioning technology based on the steepest descent method has better positioning accuracy.
文章引用：黄海波, 周蓉, 王文锐, 宋伟, 田龙斌. 基于最速下降法的室内定位技术研究[J]. 光电子, 2017, 7(1): 28-33. https://doi.org/10.12677/OE.2017.71005

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