本論文探討混合式定位系統，利用擴展型卡爾曼濾波器整合包含無線通訊系統之訊號抵達時間與慣性量測訊號。慣性定位是以量測自身角速率與加速度，利用航位推算法推估行進方位與行進路徑，並估測出目前之位置，完全不依賴外界資訊。 但其誤差因針對量測值進行積分，而連同感測器之雜訊或偏移量一同累加而導致估測誤差，隨時間增長之下，估測結果越來越不可信任；混合式系統則結合無線定位來抑制累增之估測偏差，並以慣性量測來更精準的預測位置，以輔助定位系統的估測值。
無線通訊系統之中，利用已知基地台資訊與抵達時間 (Time of Arrival, TOA) 資訊，藉由三角定位法或非線性估測系統進行目標定位。 但受到非視線傳播問題所影響，抵達時間量測值所呈現之訊號，相當於加上一個指數分布誤差。 針對其影響，經由已提出之改良型偏移式卡爾曼濾波器雖能抑制抵達時間之非視線傳播路徑成分，但該架構乃針對單一的基地台量測數值進行處理，針對額外裝置可進行輔助以進行更有效之抑制並無探討。 利用慣性系統免疫於外界環境影響之特性，對於無線訊號的非視線傳播誤差處理有所幫助，而量測之慣性量能有效地對無線量測值進行預測。 因此本論文提出混合式定位系統，並以混合偏移式擴展型卡爾曼濾波器作為抑制非視線傳播誤差並同時進行混合定位，利用整合慣性系統較為有效提供預測值之優勢，將混合偏移式擴展型卡爾曼濾波器之預測結果以回饋 (feedback) 方式來輔助非視線傳播誤差抑制。
在論文的最後，以電腦模擬以整合包含無線通訊與慣性量測的混合式架構之下，對所提出之抑制非視線傳播誤差的架構進行比較與探討。利用 IEEE 802.15.3a 之超寬頻無線通道模型之參數，以MATLAB 進行模擬。 模擬中針對目標固定移動速率、轉彎、基地台的非視線傳播誤差狀態改變的情境，透過誤差值比較，呈現所提出之架構對於環境變化的敏感程度與適用情況。 模擬結果顯示所提出之混合式定位系統能有效抑制非視線傳播誤差，達到較佳的定位與抑制成果。

The thesis is mainly focused on a hybrid location system, which processes wireless and inertial measurements by extended Kalman filtering. Inertial location system is usually used with Dead-Reckoning method, which calculates the present location and heading direction from a previous known state by using measurements of accelerometer and gyroscope, which have immunity from the environment. The system estimates the position by integrates the measurements of sensors, resulting in high accuracy during a short period. However, the unreliability grows with time due to the bias effect on sensors. By combining the wireless location and inertial system, the uncertainty of estimation can be reduced. In wireless communications, the locations of base stations and the times of signal arrival can be used in locating a mobile station. However, signal propagation could be blocked by objects. The non-line of sight (NLOS) effects cause arrival delay and is usually modeled as exponential distributions. Previously, the improved biased Kalman filters were designed to mitigate the NLOS effect in base station measurements. The system design has difficulty in accommodating inertial measurements. The inertial has immunity to the environment. The property is of help in the NLOS mitigation. Therefore, we propose a hybrid location system that integrating the wireless and inertial measurements by using a hybrid biased extended Kalman filter at the stage of positioning. The system provides better prediction with the assistance of enviroment-free inertial measurements. The NLOS mitigation with prediction feedback scheme results in better mitigation performance. Simulations of different situations have been conducted based on parameters in the IEEE 802.15.3a ultra-wideband environment. The performance differences between the proposed method and other approaches show that inertial assisted system effectively reduces the NLOS effects. Also, the proposed hybrid location system has more efficient mitigation performance and better tracking results.

誌謝. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
圖次. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
表次. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
1 緒論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 研究背景. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 研究動機. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 論文架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 定位系統. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1 估測系統. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.1 卡爾曼濾波器. . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.2 擴展型卡爾曼濾波器. . . . . . . . . . . . . . . . . . . . . . . 7
2.2 超寬頻無線定位. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2.1 時間應用定位法. . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.2 非視線傳播誤差. . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 慣性定位. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3.1 慣性量測. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.3.2 慣性定位法. . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3 混合偏移式擴展型卡爾曼濾波器. . . . . . . . . . . . . . . . . . . . . . . . 29
3.1 混合擴展型卡爾曼濾波器. . . . . . . . . . . . . . . . . . . . . . . . . 30
3.2 混合偏移式擴展型濾波器架構. . . . . . . . . . . . . . . . . . . . . . 32
3.2.1 非視線傳播鑑別. . . . . . . . . . . . . . . . . . . . . . . . . 33
3.2.2 非視線傳播抑制. . . . . . . . . . . . . . . . . . . . . . . . . 34
4 系統模擬及分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.1 模擬環境與參數. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.1.1 超寬頻無線定位系統. . . . . . . . . . . . . . . . . . . . . . . 37
4.1.2 慣性感測器之參數. . . . . . . . . . . . . . . . . . . . . . . . 38
4.2 物體運動模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.3 定位效能分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.3.1 分析之情境與重點. . . . . . . . . . . . . . . . . . . . . . . . 41
4.3.2 分析結果. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.4 分析總結. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5 總結與未來展望. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
參考文獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

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