Indoor Location Tracking Using Inertial Navigation Sensors and Radio Beacons
We consider the problem of real-time sensing and tracking the location of a moving cart in an indoor environment. To this end, we propose to combine position information obtained from an inertial navigation system (INS) and a short-range wireless referenc
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Abstract. We consider the problem of real-time sensing and tracking the location of a moving cart in an indoor environment. To this end, we propose to combine position information obtained from an inertial navigation system (INS) and a short-range wireless reference system that can be embedded into a future“network of things”. The data produced by the INS lead to accurate short-term position estimates, but due to the drifts inherent to the system, these estimates perform loosely after some time. To solve this problem, we also generate estimates with a wireless reference system. These radio-based estimates can be used as accurate long-term position estimates because their accuracy improves over time as the channel fading can be averaged out. We use a data fusion algorithm based on Kalman filtering with forward/backward smoothing to optimally combine the short- and long-term position estimates. We have implemented this localization system in a real-time testbed. The measurement results, which we obtained using the proposed method, show considerable improvements in accuracy of the location estimates.
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Introduction
Real-time position localization of moving objects in an indoor environment is an important enabling technology for realizing the vision of the“internet of things” and will thus create numerous novel location-aware services and applications in various market segments. In the retail industry, for example, shopping carts equipped with shopping assistants enriched with additional location sensing means can guide customers through the store, provide them with location-based product information, and alert them to promotions and personalized discounts as they walk through the aisles. However, customer satisfaction, and thereby the success of this advanced shopping service, depends crucially on the achievable position accuracy. Moreover, the price of the shopping-cart tracking solution should be low enough to keep its attractiveness in the eyes of retailers. Location tracking in an indoor environment can be done with various techniques based on mechanical, acoustical, ultra-sonic, optical, infrared, inertial, or
Pedro Coronel is now with the Communication Technology Laboratory, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland. Simeon Furrer is now with Broadcom Corporation, Sunnyvale, CA, USA.
C. Floerkemeier et al. (Eds.): IOT 2008, LNCS 4952, pp. 325–340, 2008. c Springer-Verlag Berlin Heidelberg 2008
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radio-signal measurements. Localization algorithms in radio-based systems are frequently implemented measuring signal strength [1], angle of arrival, or time of arrival. As the radio beacons are deployed at known positions, triangulation or a signature method yield the location of the moving cart. As far as the radio technology is concerned, the short-range wireless personal-area and sensor network technology as specified by the IEEE 802.15.x standardization body and the ZigBee alliance are well-suited for obtaining low-cost implementations. However, the IEEE 802.
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