Conference Paper

Mobile location finding using ATSC mobile/handheld digital TV RF watermark signals

DOI: 10.1109/VETECF.2010.5594101 Conference: Vehicular Technology Conference Fall (VTC 2010-Fall), 2010 IEEE 72nd
Source: IEEE Xplore


This paper investigates the use of ATSC M/H digital television (DTV) signal for location finding. In comparison to satellite based location finding system, DTV signals have higher field strength, wider bandwidth, lower frequency band, and DTV transmission towers are pervasively available everywhere. They can be used for indoor and mobile location finding in major cities where satellite based system might not function well. The ATSC receiver can obtain the multiple transmitter impulse responses and signal arrival times using the embedded RF watermark (RFWM) signal, and then derives its geographic coordinates based on the position of ATSC transmitters. As a critical step of this process, the transmitter identification in mobile environment has significant impact on the overall accuracy of location finding. In this paper, we present extensive analytical and simulation results to demonstrate the performance of RFWM technology over mobile channels.

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    ABSTRACT: Owing to the characteristic of single frequency network (SFN) and non-line of sight (NLOS) environment, base station (BS) identification becomes a prominent problem in SFN positioning systems. In this work, a universal BS identification algorithm is proposed for any DTV standard. The basic idea is to formulate the base station identification problem as a data classification which is then solved by the least distance classifier. The state prediction model is utilized to estimate kinematics parameters and thus decrease the system hardware requirement. In order to obtain accurate state prediction for BS identification, an interacting multiple model (IMM) method is adopted to mitigate the NLOS effect for performance improvement. Because of close relation between the position estimation and BS identification, the proposed method is more effective as compared to some existing methods. Simulation results show that the proposed algorithm can perform well in both unfixed BS set and NLOS environments.
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