基於最小最大遺憾估測之行動台定位

Mobile Location Based On MiniMax Regret Estimation

曾得富(Te-Fu Tseng)

指導教授 ： 沈志昌

嶺東科技大學/資訊學院/資訊科技應用研究所/碩士(2014年)

摘要

全球定位系統(GPS)，是最普遍的室外定位系統，但在衛星信號覆蓋率較差的環境無法保持視線距離時，會降低其準確性，因此無線感測定位近年來成為相當熱門的研究項目，其定位技術分別為接收訊號強度(RSS, Received Signal Strength)、到達時間((TOA, Time of Arrival)、到達時間差(TDOA, Time Difference of Arrival)以及到達角度(AOA, Angel of Arrival)，而在其定位性能上，因為有著非視線距及多重路徑的影響，所以要以定位演算法來降低其誤差和提高精準度。以RSS為訊號模型因為不需要時間同步，且其定位估測方法容易實施，在實際建置成本上，會比其他定位方法低，可直接透過訊號強度衰減來轉換成距離資訊，同時定位出目標物。因此，本研究運用RSS定位技術，透過比較定位演算法探討在受干擾環境下的定位精準度。
蜂巢系統下的行動台定位對於商業以及人身安全有著重要的需求。本文提出基於混合RSS/AOA的行動台估測算法運用於低訊雜比和非視線誤差情況下來進行位置估測。為了減少估測誤差，一個混合RSS/AOA架構下的線性最小最大遺憾估測被提出，模擬結果中證明了該估測算法明顯的優於其他的算法。

關鍵字

無線定位 ； 接收訊號強度 ； 到達角度 ； 最小平方法 ； 最小最大遺憾估測

並列摘要

The Global Positioning System (GPS) is a successful and best satellite navigation system that provides mobile location in all environments of outdoor. But it cannot keep the best line of sight, and the accuracy of location will be degraded in the environment of poor satellite signal. The position technologies include received signal strength (RSS), time of arrival (TOA), time difference of arrival (TDOA), and angle of arrival (AOA). However, the non-line of sight and the multiple path will effect positioning performance. A positioning algorithm is necessary to reduce the errors and improve the estimation accuracy. Furhermore, the RSS does not require time synchronization. Therefore, we can easy to get the positioning estimation. In establish and development costs, RSS is lower than other positioning methods; and it throughs the signal strength to transfer the distance, and the location of the target can be obtained. This study is based on RSS positioning technology to discuss the accurate algorithms and signal model by positioning algorithms.
Estimating a location of mobile station is considerable interest in wireless cellular systems. This paper deals with a hybrid (RSS)/(AOA) mobile location estimation under relatively low signal-to-noise ratio (SNR) and moderately non-line of sight (NLOS) scenarios. To reduce position estimation errors, a robust estimator for hybrid RSS/AOA location systems is proposed by using the minimax regret error criterion. Simulation results demonstrate that the proposed estimator significantly outperforms the other least squares estimator.

並列關鍵字

wireless location ； received signal strength (RSS) ； angle-of-arrival(AOA) ； least square (LS) ； minimax regret estimator

參考文獻

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