A computationally efficient approach for hidden-Markov model-augmented fingerprint-based positioning

作者：Roth John^*; Tummala Murali; McEachen John

来源：International Journal of Systems Science, 2016, 47(12): 2847-2858.

DOI：10.1080/00207721.2015.1034301

• computational complexity
• geolocation
• hidden-Markov model
• maximum-likelihood
• timing adjust
• fingerprinting

This paper presents a computationally efficient approach for mobile subscriber position estimation in wireless networks. A method of data scaling assisted by timing adjust is introduced in fingerprint-based location estimation under a framework which allows for minimising computational cost. The proposed method maintains a comparable level of accuracy to the traditional case where no data scaling is used and is evaluated in a simulated environment under varying channel conditions. The proposed scheme is studied when it is augmented by a hidden-Markov model to match the internal parameters to the channel conditions that present, thus minimising computational cost while maximising accuracy. Furthermore, the timing adjust quantity, available in modern wireless signalling messages, is shown to be able to further reduce computational cost and increase accuracy when available. The results may be seen as a significant step towards integrating advanced position-based modelling with power-sensitive mobile devices.

• 出版日期2016-9-9
• 单位中国人民解放军海军大连舰艇学院