A Survey of Fingerprint-Based Outdoor Localization

• Published in: IEEE Communications surveys and tutorials 2016, Vol.18 (1), p.491-506
• Main Authors: Quoc Duy Vo, De, Pradipta
• Format: Article
• Language: English
• Subjects: Accuracy; Content Based Image Retrieval; Database Search; Devices; Energy Efficiency; Feature extraction; Fingerprint recognition; Fingerprinting; Localization; Mobile communication systems; Mobile handsets; Outdoor; Outdoor Positioning; Pattern Matching; Position (location); Searching; Sensors; Signal based Positioning; Signatures; Smartphone Sensing; Tutorials; Visualization
• ISSN: 1553-877X; 2373-745X
• DOI: 10.1109/COMST.2015.2448632

A growing number of sensors on smart mobile devices has led to rapid development of various mobile applications using location-based or context-aware services. Typically, outdoor localization techniques have relied on GPS or on cellular infrastructure support. While GPS gives high positioning accuracy, it can quickly deplete the battery on the device. On the other hand, base station based localization has low accuracy. In search of alternative techniques for outdoor localization, several approaches have explored the use of data gathered from other available sensors, like accelerometer, microphone, compass, and even daily patterns of usage, to identify unique signatures that can locate a device. Signatures, or fingerprints of an area, are hidden cues existing around a user's environment. However, under different operating scenarios, fingerprint-based localization techniques have variable performance in terms of accuracy, latency of detection, battery usage. The main contribution of this survey is to present a classification of existing fingerprint-based localization approaches which intelligently sense and match different clues from the environment for location identification. We describe how each fingerprinting technique works, followed by a review of the merits and demerits of the systems built based on these techniques. We conclude by identifying several improvements and application domain for fingerprinting based localization.