CAJ | 학술논문

室内无线网络信号强度在一定程度上表现了接收器与信号发射源的距离信息，因此在移动设备上不添加任何额外接收设备而利用无线网络信号进行室内定位是目前的一种主流技术。但由于无线网络信号容易受到复杂的室内环境干扰，基于无线网络信号的定位结果容易产生较大的误差。文章提出了一种基于无线网络信号构成的指纹室内定位技术，用传统的指纹室内定位技术结合稀疏表示方法，利用稀疏字典提取指纹中的主特征指纹从而分离大部分的指纹噪声，再利用分离后的指纹进行定位。实验结果表明，与传统算法相比，该算法可将定位精度提高约20%。
실내무선망락신호강도재일정정도상표현료접수기여신호발사원적거리신식，인차재이동설비상불첨가임하액외접수설비이이용무선망락신호진행실내정위시목전적일충주류기술。단유우무선망락신호용역수도복잡적실내배경간우，기우무선망락신호적정위결과용역산생교대적오차。문장제출료일충기우무선망락신호구성적지문실내정위기술，용전통적지문실내정위기술결합희소표시방법，이용희소자전제취지문중적주특정지문종이분리대부분적지문조성，재이용분리후적지문진행정위。실험결과표명，여전통산법상비，해산법가장정위정도제고약20%。
It is feasible to implement the indoor localization techniques using wireless received signal strengths(RSSs) on the mobile devices since the RSSs indicate the information of distance between a transmitter and a receiver. However, the variation of RSSs severely reduces the localization accuracy due to the multipath effect and the unpredictable change of indoor environments. On this basis, a ifngerprint-based indoor localization algorithm was designed leveraging the theory of sparse representation. In our approach, the variations were separated from the feature fingerprints using the sparse dictionary. Experiments were conducted for evaluating the performance of the algorithm in the real scenarios. Compared to traditional algorithms in indoor localization, the average localization error is reduced by 20%.