Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Wi-Fi Positioning Metrics <s> The proliferation of mobile computing devices and local-area wireless networks has fostered a growing interest in location-aware systems and services. In this paper we present RADAR, a radio-frequency (RF)-based system for locating and tracking users inside buildings. RADAR operates by recording and processing signal strength information at multiple base stations positioned to provide overlapping coverage in the area of interest. It combines empirical measurements with signal propagation modeling to determine user location and thereby enable location-aware services and applications. We present experimental results that demonstrate the ability of RADAR to estimate user location with a high degree of accuracy. <s> BIB001 </s> Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Wi-Fi Positioning Metrics <s> We present the design and implementation of the Horus WLAN location determination system. The design of the Horus system aims at satisfying two goals: high accuracy and low computational requirements. The Horus system identifies different causes for the wireless channel variations and addresses them to achieve its high accuracy. It uses location-clustering techniques to reduce the computational requirements of the algorithm. The lightweight Horus algorithm helps in supporting a larger number of users by running the algorithm at the clients.We discuss the different components of the Horus system and its implementation under two different operating systems and evaluate the performance of the Horus system on two testbeds. Our results show that the Horus system achieves its goal. It has an error of less than 0.6 meter on the average and its computational requirements are more than an order of magnitude better than other WLAN location determination systems. Moreover, the techniques developed in the context of the Horus system are general and can be applied to other WLAN location determination systems to enhance their accuracy. We also report lessons learned from experimenting with the Horus system and provide directions for future work. <s> BIB002 </s> Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Wi-Fi Positioning Metrics <s> Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented. <s> BIB003 </s> Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Wi-Fi Positioning Metrics <s> Indoor localization is of great importance for a range of pervasive applications, attracting many research efforts in the past two decades. Most radio-based solutions require a process of site survey, in which radio signatures are collected and stored for further comparison and matching. Site survey involves intensive costs on manpower and time. In this work, we study unexploited RF signal characteristics and leverage user motions to construct radio floor plan that is previously obtained by site survey. On this basis, we design WILL, an indoor localization approach based on off-the-shelf WiFi infrastructure and mobile phones. WILL is deployed in a real building covering over 1600 m2, and its deployment is easy and rapid since site survey is no longer needed. The experiment results show that WILL achieves competitive performance comparing with traditional approaches. <s> BIB004 </s> Indoor Fingerprint Positioning Based on Wi-Fi: An Overview <s> Wi-Fi Positioning Metrics <s> The survey of WiFi access points (APs) locations and their propagation parameters (PPs) is a time and labour consuming process, which makes WiFi positioning impractical. In this paper, a novel crowdsourcing method is introduced. The proposed method is used for automatic AP localization and PPs estimation by employing an inertial navigation solution, such as Trusted Portable Navigator (T-PN). The proposed system runs on smartphones, from which it builds and updates the database autonomously and adaptively to account for the dynamic environment. A WiFi positioning method, based on the generated database, is also discussed. The proposed system is validated by both simulated and experimental tests. <s> BIB005
With the development of Wi-Fi positioning technology, many Wi-Fi positioning systems have been proposed-from early systems such as RADAR BIB001 and Horus BIB002 , to systems using advanced technology such as WILL BIB004 and Lifts BIB005 . These systems, including the various techniques and methods researchers have proposed, all view accuracy as the primary measuring rule of indoor positioning technology. However, it is not enough to measure how well an indoor positioning technology is operating by only using accuracy to judge. According to reference BIB003 , the Wi-Fi positioning system has the following several aspects of metrics. (1) Accuracy/Measurement Uncertainty Accuracy, or measurement uncertainty, is the primary measure of the indoor positioning method. The higher the accuracy, the better the positioning effect of the method, thus the greater the likelihood of the method being more suitable for indoor positioning. According to Mautz  , instead of accuracy, measurement uncertainty is now used for the quantification of a standard deviation. However, many researchers still use accuracy in their studies so as to avoid misunderstanding, we use the conventional term 'accuracy' in this paper. Mautz  thought that "positioning accuracy" should be understood as the degree of conformance of an estimated or measured position at a given time to the true value, expressed for the vertical and horizontal components at the 95% confidence level. Of course, due to various application environments, each indoor positioning system has different requirements for accuracy.