论文标题
基于RSS指纹的非线性位置估计的内核方法
A Kernel Method to Nonlinear Location Estimation with RSS-based Fingerprint
论文作者
论文摘要
本文提出了非线性位置估算,以推断持有智能手机的用户的位置。我们考虑一个具有$ M $的网格点的较大位置,每个网格点都标有一个独特的指纹,该指纹由接收的信号强度(RSS)值组成,该值从$ n $ n $ bluetooth低能(BLE)信标中测量。鉴于智能手机观察到的指纹,可以通过从数据库中注册的指纹列表中找到TOP-K相似的指纹来估算用户的当前位置。除了环境因素之外,持有智能手机的动态性是指纹测量变化的另一个来源,但是由于人手在线检测期间,由于人手持有的动态智能手机位置而导致的指纹可变性的研究并不多。为此,我们使用内核方法提出了非线性位置估计。具体而言,我们提出的方法包括两个步骤:1)选择信标的子集对信标的子集不敏感,该子集对持有位置的细微变化不敏感,而2)一种内核方法,用于计算观察到的信号的这一子集与数据库中注册的所有指纹之间的相似性。基于在复杂建筑物中收集的大规模数据的实验结果表明,与最先进的方法相比,我们提出的方法的性能获得了可观的性能。由从信标收集的信号信息组成的数据集可在线获得。
This paper presents a nonlinear location estimation to infer the position of a user holding a smartphone. We consider a large location with $M$ number of grid points, each grid point is labeled with a unique fingerprint consisting of the received signal strength (RSS) values measured from $N$ number of Bluetooth Low Energy (BLE) beacons. Given the fingerprint observed by the smartphone, the user's current location can be estimated by finding the top-k similar fingerprints from the list of fingerprints registered in the database. Besides the environmental factors, the dynamicity in holding the smartphone is another source to the variation in fingerprint measurements, yet there are not many studies addressing the fingerprint variability due to dynamic smartphone positions held by human hands during online detection. To this end, we propose a nonlinear location estimation using the kernel method. Specifically, our proposed method comprises of two steps: 1) a beacon selection strategy to select a subset of beacons that is insensitive to the subtle change of holding positions, and 2) a kernel method to compute the similarity between this subset of observed signals and all the fingerprints registered in the database. The experimental results based on large-scale data collected in a complex building indicate a substantial performance gain of our proposed approach in comparison to state-of-the-art methods. The dataset consisting of the signal information collected from the beacons is available online.