綜觀現行水深測量作業流程，可能面臨垂直基準偏移、資料缺漏、資料處理耗時等問題。傳統水深測量作業須改正湧浪、動態吃水及潮汐等垂直變化因子；而潮位修正仰賴潮位觀測資料，其觀測量受陸域地表變動影響，更可能衍生基準偏移的問題。以橢球面為基準的測深，因前述垂直變化因子在化算海床橢球高的過程中將會一併抵銷，可避免諸多誤差來源以及基準偏移問題。另外，小型無人船已被證實可以搭載多音束測深儀（multibeam echosounder, MBES）執行測量作業，解決受限於場域造成資料缺漏的問題。然而MBES龐大的測深資料帶來大量資料處理人力與時間的需求，也使自動化處理測深資料的方法有其必要。本研究利用Otter Pro 無人船搭載Norbit iWBMS多音束測深儀，在臺南安平亞果遊艇港、高雄興達漁港以及宜蘭烏石遊艇港等場域進行水深測量。測得的原始資料以橢球高為基準面之測深模式處理：定位與姿態透過 Applanix POSpac 軟體解算後處理解；聲速透過聲速剖面儀（sound velocity profiler, SVP）之資料，以聲線追跡（ray-tracing）演算法進行改正；姿態改正部分則包含在直接地理定位過程。在點雲的自動化雜訊過濾方面，本研究結合quantile filter、多解析度的M-Estimator，以及Combined Uncertainty and Bathymetry Estimator (CUBE) 演算法產製數值高程模型，作為最終篩選雜訊的依據。為確保自動化過濾之成果品質，本研究亦標記需人工介入處理的區域。最後，本研究之成果以人工利用CARIS HIPS and SIPS 軟體套件處理的測深資料進行驗證，其中GNSS tide 的成果用來驗證本研究以橢球高為參考面的測深成果的正確性，同時評估點雲過濾之成效；而透過潮位修正到最低天文潮位面（Lowest Astronomical Tide, LAT）的成果加上離距模型（Separation Model, SEP），則用來驗證以橢球面為參考面測深之成效。在GNSS/INS整合解方面，研究成果顯示鬆耦合（loosely-coupled）與緊耦合（tightly-coupled）的成果並無顯著差異，但緊耦合解之精度略高於鬆耦合解的精度，故優先使用緊耦合解。在測深資料處理方面，在安平亞果遊艇港、興達漁港以及烏石遊艇港分別有95.51%、99.82%、97.34%的區域可自動化過濾。其成果與GNSS tide 人工處理成果的較差平均值在三個實驗場域均為 -0.007 m，但較差標準差的平均介於0.014 m到0.166 m。結果顯示本研究方法與GNSS tide 成果接近，惟在雜訊過濾方面，與人工處理之成果仍有些微差異。至於與CARIS經潮位修正之成果比較，在三個測區分別發現約0.07 m、0.25 m 以及-0.26 m的系統性偏差，推測與當地LAT基準、相對定位基站之高程基準或無人船垂直向定位精度之極限有關。

Reviewing the current bathymetric survey workflows, there can be issues such as vertical datum shifts, data gaps, and time-consuming data processing. Traditional bathymetry must correct for vertical factors such as heave, dynamic draft, and tides. Tidal corrections rely on the observations from tide gauges, which can be affected by land motions, potentially inducing datum shifts. Ellipsoidally referenced bathymetry can avoid multiple error sources and datum shift issue, as the vertical factors can be eliminated in the process of calculating seafloor ellipsoid heights. In addition, small-sized unmanned surface vehicles (USVs) equipped with multibeam echosounders (MBES) have been proven capable of performing bathymetric surveying, addressing data gaps caused by site constraints. However, the large amount of the bathymetric data is often laborious for processing, prompting the necessity of automatic data-cleaning methods. This study utilizes the Otter Pro USV equipped with a Norbit iWBMS multibeam echosounder to conduct bathymetric surveys in An-ping Yacht Harbor in Tainan, Xing-da Fishery Harbor in Kaohsiung, and Wu-shi Yacht Port in Yilan. The raw data are processed in ellipsoidally referenced bathymetry scheme: the positioning and attitude are computed by Applanix POSpac software; sound velocity was corrected using data from the sound velocity profiler (SVP) with the ray-tracing algorithm; attitude corrections were included in the direct georeferencing process. For the automatic data-cleaning processing, this study combined the quantile filter, multi-resolution M-Estimator, and the Combined Uncertainty and Bathymetry Estimator (CUBE) algorithms to produce digital elevation models as the basis for the final outlier identifications. To ensure the quality of the automatic data-cleaning results, this study marks out the areas requiring manual intervention. Finally, the results of this study are validated by manually processed bathymetric data using CARIS HIPS and SIPS software. The GNSS tide results are used to verify both the correctness of the ellipsoidally referenced depths and the effectiveness of the data-cleaning process from the proposed method. Additionally, the results corrected to the Lowest Astronomical Tide (LAT) with a separation model (SEP) are used to verify the effectiveness of ellipsoidally referenced bathymetry. In terms of GNSS/INS integration solutions, the study results show no significant differences between loosely-coupled and tightly-coupled solutions. Nonetheless, the precision of tightly-coupled solutions is slightly higher than that of loosely-coupled solutions; thus, tightly-coupled solutions were prioritized. In terms of bathymetric data processing, the areas that can be automatically filtered are 95.51%, 99.82%, and 97.34% in Anping, Xing-da, and Wu-shi, respectively. The average differences between the results and the manually processed results using the GNSS tide are -0.007 m for all the three sites, while their average standard deviations of differences range from 0.014 m to 0.166 m. The results indicate that the proposed method provides similar results to those from the GNSS tide. In comparison to CARIS results corrected by tide, constant biases of approximately 0.07 m, 0.25 m, and -0.26 m are found in the three sites. Chances are that they are originated from either the local LAT datum shifts, errors in the elevation of the base stations, or the limits of the vertical positioning accuracy.

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