基于智能手机无线信号和图像距离感知融合的室内定位算法

针对于目前面向个人使用的手机室内定位精度低、效果差，且成本较高难以拓展的问题，提出了一种利用普通智能手机作为硬件设备，融合Wi-Fi无线信号和图像数据，通过双层过滤的方式对用户进行高精度室内定位的算法。算法分为线下阶段和线上阶段。在线下阶段，对目标场地建立坐标系，在坐标系多个目标位置进行Wi-Fi采样并建立指纹库，同时对环境进行拍照取样并抽取图像特征。在线上阶段，通过实时获取的Wi-Fi信息进行第一层过滤，以确定当前用户可能的位置区间；然后，结合提出的一种距离补偿算法对用户手机当前捕获的图像进行特征提取，在第一层过滤的基础上，确定用户的精准位置。在实际场地进行的实验表明，相比传统Wi-Fi及二维图像定位方法，该算法能够在探测接入点（AP）数量较少及室内场景相似的情况下提高室内定位精度，可以应用于一般室内定位应用或结合基于位置的服务（LBS）应用。

Ensemble smartphone indoor localization algorithm based on wireless signal and image analysis

Since the present performance of smartphone based personal indoor localization is still far from satisfaction with problems in accuracy, cost and etc., a duel-step filtering indoor localization algorithm fusing Wi-Fi fingerprints and images implemented on devices like smartphones was proposed in this paper. This algorithm comprised of offline stage and online stage. On the offline stage, Wi-Fi fingerprints were collected and a fingerprint library sampled in different positions in the coordinate system was constructed. Photos were taken in that stage to extract the image features. On the online stage, the first filter process was to determine the possible area where the user is currently by using Wi-Fi information captured in real-time. Then a distance compensation algorithm was proposed in this paper to extract features of the real-time image taken by the user to determine the exact localized position. Experimental results show that this algorithm can effectively improve localization precision compared with traditional Wi-Fi and image based localization methods in environments with fewer APs (Access Points) and similar layouts, thus is capable for general localization or LBS (Location-Based Service) relevant applications.