室內空間定位系統中實測點選擇演算法

Measure Point Selection Algorithms for Wireless Indoor Positioning Systems

陳大鈞(Ta-Chun Chen)

指導教授 ： 林永松

國立臺灣大學/管理學院/資訊管理學研究所/碩士(2004年)

https://doi.org/10.6342/NTU.2004.01961

摘要

近年來，室內空間中使用者定位方面的服務逐漸成為一項熱門的議題，同時IEEE802.11無線網路技術之成熟，也使其成為室內空間定位上的首選。而由於802.11之RF訊號易受到室內空間中的障礙物以及人體的影響而衰減，因此傳統的室外空間定位演算法，如三角定位法是不適用的。

為了能在室內空間中精確地定位，許多研究提出為室內空間事先建立一個場地訊號測量資訊的資料庫是有必要的。在實際定位過程中，藉由比對訊號資料庫與行動端點收到各AP的訊號強度值，可得出該行動端點最有可能的定位點。然而實際測量全部各點的訊號值卻是非常耗費人力的。因此，本研究的目標即在於，透過精心選擇適量的實測點並收集其訊號實測值，輔以良好的訊號推估演算法，可藉精確地推估出其餘各點的訊號強度值，並減少人力的浪費。

本研究分為兩階段，第一個階段提出透過實測值以推測出推估值之最佳訊號強度推估演算法;第二階段則根據第一階段的訊號推估演算法，以及給定的實測密度，使用求解組合性最佳化的模擬退火法以求解最佳的實測點位置組合。

關鍵字

IEEE802.11 ； 最佳化 ； 室內定位演算法 ； 室內定位 ； 組合性最佳化 ； 模擬退火法 ； 訊號強度

並列摘要

Recently, the service of indoor positioning system has gradually become a hot issue; and with the maturation of IEEE 802.11 wireless technology, it has been the first choice for indoor positioning system. Owing to the sensitivity of RF signal of 802.11 which may attenuated by obstacles and human body, traditional outdoor positioning algorithm, such as triangle positioning algorithm, is not suitable to use for indoor positioning.

In order to accurately position in indoor space, many researches have pointed out that a previously built RSSI (Received Signal Strength Indicator) database is necessary. By comparing the RSS vector received at mobile nodes with RSSI database, we can precisely position the location of mobile users. However, collecting RSS for all grids of indoor space costs lots of human resource. Hence, the purpose of this thesis is to propose a method, which selects measure points elaborately, and collocates with a nice RSS inference algorithm, and then we can build up well RSSI database with relatively lower cost.

In this research we proposed a method that selects suitable quantity of measure points at elaborately selected locations, and infers the signal strength of the other points based on these selected measure points to reduce signal strength collecting cost.

並列關鍵字

Optimization ； Combinatorial Optimization ； Simulated Annealing ； Indoor position ； Signal Strength ； Indoor Positioning Algorithm ； IEEE 802.11

參考文獻

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