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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%。
Indoor wireless network signal strength to a certain extent, the performance of the receiver and signal source distance information, so the mobile device does not add any additional receiving equipment and the use of wireless network signals for indoor positioning is currently a mainstream technology. However, because wireless network signals are easily disturbed by complicated indoor environments, the positioning results based on wireless network signals are prone to large errors. In this paper, a fingerprint indoor positioning technology based on wireless network signal is proposed. With the traditional fingerprint indoor positioning technology combined with sparse representation, the sparse dictionary is used to extract the fingerprint of the main fingerprint to separate most of the fingerprint noise. Fingerprint positioning. Experimental results show that compared with the traditional algorithm, the proposed algorithm can improve the positioning accuracy by about 20%.