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題名 | 基於資料融合的長基線精確水下定位=Long Baseline Precise Underwater Positioning through Data Fusion |
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作 者 | 陳信宏; 周佑誠; 邱楫文; 王兆璋; | 書刊名 | 中國造船暨輪機工程學刊 |
卷期 | 34:3 2015.08[民104.08] |
頁次 | 頁145-154 |
分類號 | 444.9 |
關鍵詞 | 長基線系統; 資料融合; 水下定位; 卡曼濾波; Long baseline system; Data fusion; Underwater positioning; Kalman Filtering; |
語文 | 中文(Chinese) |
中文摘要 | 精確定位對於達成水下載具導航扮演極重要的角色,當前雖已經發展許多水下定位儀器與方法,但只有極少數的單一系統能夠提供水下載具可靠的三維座標。長基線定位系統雖然可以量測水下載具三維絕對座標,但卻也存在資料更新緩慢的問題,必須整合其他感測資料,才能提昇長基線系統定位水下載具的精度與可靠度。本研究透過數值模擬與實海域定位實驗量測,探討長基線系統之水下目標物定位精度,並探討其定位誤差來源。為了有效評估長基線定位精度,本研究於水面工作船裝載長基線收發器與GPS接收器,分別透過長基線定位與GPS定位量測收發器之絕對位置,並以GPS定位結果做為參考基準,以評估長基線系統利用斜距量測之定位估算精度。根據實驗數據分析結果可知,長基線定位誤差的主要來源在於無法連續收到應答器的回訊。利用卡曼濾波理論,整合長基線系統與速度資訊,並進行資料融合運算來獲得水下載具的收發器位置,可大幅提升水下目標物之定位精度。 |
英文摘要 | Precise positioning is crucial for the success of navigation of underwater vehicles. At present, different instruments and methods are available for underwater positioning but few of them are reliable for three-dimensional position sensing of underwater vehicles. Long baseline (LBL) positioning is the standard method for three-dimensional underwater navigation. However, the accuracy of LBL positioning suffers from its own drawback of relatively low update rates. The integration of additional sensing measurements in a LBL navigation system can improve the accuracy in positioning an underwater vehicle. This study performed an experiment to investigate the accuracy of LBL positioning through data fusion. A GPS receiver and a bottom-mounted LBL transceiver are installed on a ship to perform an experiment to collect LBL and GPS observations. The Kalman filter is adopted as the data fusion engine to combine LBL and velocity observations for the prediction and correction of LBL positioning. Then, the accuracy of LBL positioning is evaluated by comparing with the GPS measurements which is regarded as a true reference. The experimental results show that LBL positioning accuracy degrades seriously when the reply signal from the transponder is interrupted partially. The experimental results also show that the accuracy of LBL positioning can be significantly improved by incorporating velocity measurements through data fusion with Kalman filtering. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。