由於全球導航衛星系統（global navigation satellite system, GNSS）的訊號脆弱性，該系統已被調查並顯示出射頻干擾（radio frequency interference, RFI）或地面環境上不可預測的因素可能會降低或中斷全球導航衛星系統服務。因此，為下一代航空運輸系統（next generation air transportation system, NextGen）計劃了替代性的定位，導航和授時（alternative positioning, navigation, and timing, APNT）策略。根據美國聯邦航空管理局（Federal Aviation Administration, FAA）提出三種APNT系統的建議，這三個系統分別是優化的距離測量設備（distance measuring equipment, DME）網絡，基於偽衛星的多邊定位和被動式廣域多邊定位(wide area multilateration, WAM)。再本論文中，我們選擇了被動式WAM定位技術成為台灣的APNT系統，並運用廣播式自動相關監視（automatic dependent surveillance-broadcast, ADS-B）1090 MHz訊號實現它的定位性能，因為ADS-B在下一代航空運輸系統中佔有重要角色。
本文在WAM系統上使用1090 MHz ADS-B Mode S ES訊號實現了到達時間差（time difference of arrival, TDOA）定位算法。因此開發了專用的ADS-B接收器來獲取該訊號。為了討論WAM定位系統的性能，提出三種影響因子進行分析討論：（1）觀測到的TDOA距離差值測量精度，（2）系統地面站於服務區域之地理幾何分布，以及（3）用於推導位置解的強健定位演算法。第一因子分析討論是使用我們自建的接收器來檢查測量TDOA距離差值的精度。第二因子分析是透過模擬預期四個地面站的部署，討論WAM的地理幾何分布情況，以調查和評估在台灣建立WAM時可能出現的問題。第三因子是根據第二因子所模擬探討出的問題，提出了一種強健式的濾波器定位演算法，以克服模擬中的導數迭代的初始位置猜測以及地理幾何分布導致不收斂與位置精度不佳的問題，而提出的強健式的濾波器定位演算法。此方法不僅是使用Chan 和 Ho的非迭代方法，而且還使用擴展卡爾曼濾波器（extended Kalman filter, EKF）方法將ADS-B訊號角度抵達(angle of arrival, AOA)測量值和ADS-B資料鏈中的氣壓高度引入TDOA系統，以獲取優化的位置估計。另外，強健式的濾波器定位演算法不僅克服了在GNSS中斷期間無法獲取初始位置信息來初始化最小平方法(least square, LS)的問題，而且還改善了系統地面站於服務區域之地理幾何分布。重要的是，本篇論文通過收集實際飛行數據並且使用提出的強健式的濾波器定位演算法展示了定位性能，最後的定位結果在系統地面站於服務區域之地理幾何分布之水平幾何稀釋因子2.82下，滿足航機在終端層之導航水平定位精度兩個標準差(95%)之307公尺，以及監視服務要求的水平定位精度在兩個標準差(95%)之92.6公尺定位性能。

The alternative positioning, navigation, and timing (APNT) strategy has been planned for the next generation air transportation system (NextGen) because of the vulnerability of the global navigation satellite system (GNSS), which has been investigated and has shown that radio frequency interference or unpredictable factors on the ground environment might degrade or interrupt GNSS service. From the Federal Aviation Administration suggestions regarding the three APNT systems, which are the optimized distance measuring equipment network, pseudolite-based multilateration, and passive wide area multilateration (WAM), for this thesis we chose the passive wide area multilateration technology and demonstrated it based on an automatic dependent surveillance-broadcast (ADS-B) 1090 MHz signal, which will be an APNT system in Taiwan due to ADS-B playing an important role in NextGen.
This thesis implemented a time difference of arrival (TDOA) positioning algorithm using the 1090 MHz ADS-B Mode S extended squitter (Mode S ES) signal on the WAM system. To assess the performance of the TDOA positioning algorithm, three actors affecting the positioning performance for implement the WAM positioning system were examined: (1) observed TDOA differential range measurement accuracy, (2) system geometry, and (3) a robust position algorithm for deriving the position solution. The first methodology uses our self-constructed receivers to examine the measurement accuracy. The second methodology simulates a scenario of expected WAM deployed using four ground stations to investigate and assess the appearance of issues that may arise when establishing WAM in Taiwan. The third methodology presents a robust filter position algorithm to overcome the issues from the simulation. The robust filter position algorithm not only uses the Chan and Ho method, but it also introduces barometric altitude and angle of arrival measurements into the TDOA system using the extended Kalman filter method to obtain the optimized position estimate. In addition, the robust filter position algorithm not only overcomes the issue of not obtaining the initial position information to initialize the iterative least square method during GNSS outage, but it also improves system geometry. Importantly, this current dissertation demonstrates positioning performance that results from using instances with HDOP ≤ 2.82 that yield a positioning root mean square error performance which meets both the RNP/RNAV 0.3 navigation requirement (95% HPE ≤ 307 m) and the WAM surveillance requirement (95% HPE ≤ 92.6 m) through the collection of actual flight data.

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