基于WLAN指纹的机身指纹数据库重构与节点定位方法

为降低指纹数据人工采集量，同时获取较高的定位精度性能，提出了一种基于WLAN指纹的飞机机身指纹数据库重构与测试节点定位方法。利用支持向量回归法重建指纹数据，利用K-means算法降低指纹采集工作量，利用优化的DBN进行RSS信息特征提取，最后建立了飞机机身WLAN指纹定位数据库，通过仿真实验对算法性能和系统进行分析和评估。实验结果表明，KNN算法中，IPDBN-54、IPDBN-41、IPDBN-26的平均定位误差分别为10.389 2、10.786 3、11.117 7。WKNN算法中，IPDBN-54、IPDBN-41、IPDBN-26的平均定位误差分别为10.290 4、10.714 3、11.103 8,IPDBN平均定位误差值最小，定位精度相对较高。对比BPNN,IPDBN平均训练时间为166.2 s,具有相对低的训练时间。优化后的深度信念网络算法对于WLAN指纹定位数据库系统建立问题具有很强的适应性，训练时间短、定位精度高。研究旨在实现试验厂房内飞机机身各部位的空间精确定位，提高效率。

Fingerprint database reconstruction and node location of aircraft structure strength test

In order to reduce the manual collection of fingerprint data and obtain high positioning accuracy, a fingerprint database reconstruction and node location of aircraft structure strength test algorithm based on WLAN fingerprint was proposed in this paper. The support vector regression method was used to reconstruct fingerprint data, K-means algorithm was used to reduce the workload of fingerprint collection, and the optimized DBN was used to extract the features of RSS information. Finally, the WLAN fingerprint location database of the aircraft body is established, and the algorithm performance and system were analyzed and evaluated through simulation experiments. The experimental results showed that the average positioning errors of IPDBN-54, IPDBN-41 and IPDBN-26 in KNN algorithm were 10.389 2, 10.786 3 and 11.117 7 respectively. In the WKNN algorithm, the average positioning errors of IPDBN-54, IPDBN-41 and IPDBN-26 were 10.290 4, 10.714 3 and 11.103 8, respectively. The average positioning error of IPDBN was the smallest and the positioning accuracy was relatively high. Compared with BPNN, the average training time of IPDBN was 166.2 s, with relatively low training time. The optimized depth belief network algorithm has strong adaptability to the establishment of WLAN fingerprint location database system, with short training time and high location accuracy. The research aims to achieve accurate spatial positioning of various parts of the aircraft fuselage in the test building and improve efficiency.