Spatial Diversity in Signal Strength Based WLAN Location Determination Systems

Literature indicates that spatial diversity can be utilized to compensate channel uncertainties such as multipath fading. Therefore, in this paper, spatial diversity is exploited for locating stationary and mobile objects in the indoor environment. First, space diversity technique is introduced for small scale motion and temporal variation compensation of received signal strength and it is demonstrated analytically that it enhances location accuracy. Small scale motion refers to movements of the transmitter and/or the receiver of the order of sub-wavelengths while temporal effects refer to environmental variations with time. A novel metric is introduced for selection combining in order to improve location accuracy through the addition of spatial diversity upon two available location determination schemes. The results are evaluated experimentally against single antenna system for reception by using low cost wireless RF devices such as motes. Alternatively, the impact of the number of location determination devices in a probabilistic WLAN network based on pre-profiling of signal strength is analyzed and it is demonstrated analytically that location accuracy improves with the number of receivers used. Spatial diversity in terms of the antenna spacing of 2lambda is evaluated and shown to provide a reduction in location determination error between 30 and 40% when compared to a single antenna system

A Robust Zero-Calibration RF-based Localization System for Realistic Environments

Due to the noisy indoor radio propagation channel, Radio Frequency (RF)-based location determination systems usually require a tedious calibration phase to construct an RF fingerprint of the area of interest. This fingerprint varies with the used mobile device, changes of the transmit power of smart access points (APs), and dynamic changes in the environment; requiring re-calibration of the area of interest; which reduces the technology ease of use. In this paper, we present IncVoronoi: a novel system that can provide zero-calibration accurate RF-based indoor localization that works in realistic environments. The basic idea is that the relative relation between the received signal strength from two APs at a certain location reflects the relative distance from this location to the respective APs. Building on this, IncVoronoi incrementally reduces the user ambiguity region based on refining the Voronoi tessellation of the area of interest. IncVoronoi also includes a number of modules to efficiently run in realtime as well as to handle practical deployment issues including the noisy wireless environment, obstacles in the environment, heterogeneous devices hardware, and smart APs. We have deployed IncVoronoi on different Android phones using the iBeacons technology in a university campus. Evaluation of IncVoronoi with a side-by-side comparison with traditional fingerprinting techniques shows that it can achieve a consistent median accuracy of 2.8m under different scenarios with a low beacon density of one beacon every 44m2. Compared to fingerprinting techniques, whose accuracy degrades by at least 156%, this accuracy comes with no training overhead and is robust to the different user devices, different transmit powers, and over temporal changes in the environment. This highlights the promise of IncVoronoi as a next generation indoor localization system.Comment: 9 pages, 13 figures, published in SECON 201

Diversity techniques for signal-strength based indoor location determination

Diversity techniques have been found in the literature to be suitable for compensating channel uncertainties such as multipath fading. In this thesis, we exploit spatial and frequency diversity techniques for improving accuracy in locating stationary and mobile objects in the indoor environment --Abstract, page iv

COMPASS: A Probabilistic Indoor Positioning System Based on 802.11 and Digital Compasses

Positioning systems are one of the key elements required by context-aware application and location-based services. This paper presents the design, implementation and anaylsis of a positioning system called COMPASS which is based on 802.11 compliant network infrastructure and digital compasses. On the mobile device, COMPASS samples the signal strength values of different access points in communication range and utilizes the orientation of the user to preselect a subset of the training data. The remaining training data is used by a probabilistic position determination algorithm to determine the position of the user. While prior systems show only limited accuracy due to blocking effects caused by human bodies, we apply digital compasses to detect the orientations of the users so that we can handle these blocking effects. After a short period of training our approach achieves an average error distance of less than 1.65~meters in our experimental environment of 312 square meters

Positioning in Indoor Mobile Systems

Non

HORUS: A WLAN-BASED INDOOR LOCATION DETERMINATION SYSTEM

As ubiquitous computing becomes more popular, the need for context-aware applications increases. The context of an application refers to the information that is part of its operating environment. Typically this includes information such as location, activity of people, and the state of other devices. Algorithms and techniques that allow an application to be aware of the location of a device on a map of the environment are a prerequisite for many of these applications. Many systems over the years have tackled the problem of determining and tracking user position. Examples include GPS, wide-area cellular-based systems, infraredbased systems, magnetic tracking systems, various computer vision systems, physical contact systems, and radio frequency (RF) based systems. Of these, the class of RF-based systems that use an underlying wireless data network, such as the IEEE 802.11 wireless network, to estimate user location has gained attention recently, especially for indoor applications. RF-based techniques provide more ubiquitous coverage than other indoor location determination systems and do not require additional hardware for user location determination, thereby enhancing the value of the wireless data network. However, using a wireless network for location determination has the challenge of dealing with the noisy characteristics of the wireless channel. Current location determination techniques for the 802.11 wireless networks suffer from these noisy characteristics, leading to coarse grained accuracy. A key feature of current techniques is the dependence on building a radio map for the area of interest and using this radio map to infer the user location. Using the radio map to infer the user location is a computationally intensive process and may consume the scarce energy resource of the mobile units. The Horus system is concerned with developing accurate methods for determining the user location with low computation requirements. Our goal is to build a location determination system that is capable of determining the user position with high accuracy, is light enough to be implemented on energy-constrained devices such as handheld computers, and is scalable to track a large number of users and to be used with large areas. We identify different causes of the wireless channel variations and we develop techniques to handle these variations. The results show that the Horus system is able to achieve accuracy significantly better than the current WLAN location determination systems. Moreover, the number of operations required to run the algorithm is better than the current systems with more than an order of magnitude