利用可預測使用者路徑輔助之非衛星定位系統

Destination-Aware Non-GPS Positioning using Predictive Contexts

楊智焙(Chih-Pei Yang)

指導教授 ： 金仲達

國立清華大學/電機資訊學院/資訊工程學系/碩士(2012年)

摘要

根據現行的手機，越來越多的基於位置的服務（LBSS）介紹，他們越來越多地影響著人們的日常生活。Glympse作為一個例子。將社交網絡與現實世界中的位置通知用戶其附近的朋友。為了得到位置，一般在這些應用中，全球定位系統正在使用。然而，GPS的能量消耗顯著由幾個以前的研究報告[19] [12]。許多研究人員然後再打的非GPS或GPS的定位策略，但在定位精度的費用。是否有一種方法來保持低功耗定位系統的精度，同時保持？
本論文的關鍵洞察力的精度的非GPS或更小的GPS定位系統，可以補償的地圖，這在今天的智能手機更是一應俱全。只要用戶的位置，可以在所要求的精度之內的地圖上標記，將是沒有必要使用任何定位傳感器。這需要知道的起始位置，目的地，以及用戶的動作。基於這一思路，我們建議在這篇論文中目標的非GPS定位系統（DNPS）。 DNPS的起點，適用於低功耗的傳感器，如手機信號塔的ID和加速度計，考慮對他/她的目的地在地圖上定位用戶。為了弄清楚用戶的目的地，DNPS利用隱馬爾可夫模型的用戶上下文關聯與他/她的日常運動行為。我們的實驗表明，基於真實用戶相比，GPS和non-GPS/less-GPS系統，DNPS是能夠降低功耗，同時保持定位精度的。

關鍵字

定位

並列摘要

With the prevailing of mobile phones, more and more location-based services (LBSs) are introduced and they increasingly influence people’s daily life. Take Glympse as an example. It associates the social network with the real world by informing users of the positions of their nearby friends. To obtain positions, generally in these applications, GPS is used. However, the energy consumption of GPS is significant as reported by several previous studies [19] [12]. Many researchers then resort to non-GPS or GPS-less positioning strategies, but at the expenses of positioning precision. Is there a way to keep the power consumption of a positioning system low while maintaining the precision?
The key insight of this thesis is that the precision of a non-GPS or less-GPS positioning system can be compensated by a map, which is readily available in today’s smart phones. As long as the position of a user can be marked on the map within the required precision, there will be no need to use any positioning sensor. This entails knowing the starting position, the destination, and the movements of the user. Based on this idea, we propose in this thesis the Destination-aware Non- GPS Positioning System (DNPS). Given a starting point, DNPS applies low-power sensors, such as cell tower id and accelerometers, to position the user on the map with consideration about his/her destination. To figure out the destination of the user, DNPS takes advantage of a Hidden Markov Model to associate the user contexts with his/her daily moving behavior. Our experiments based on real users show that, comparing to GPS and non-GPS/less-GPS systems, DNPS is able to reduce the power consumption while maintain the positioning precision.

並列關鍵字

positioning

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