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中文摘要：
深海作业技术的研究具有重要的战略意义，采矿移动机器人是深海采矿的载体，它的位置估计精度直接影响到控制质量和采矿效率。提出了一种基于伪长基线和舷往推算的组合定位方法，建立了位置估计的卡尔曼滤波器结构．针对深海底的复杂未知环境，很难获得系统状态和测量噪声准确统计信息的情况，应用自适应卡尔曼滤波算法进行数据融合，在线修正滤波器的增益。仿真验证了该方法的可行性。
英文摘要：
The research on deep seabed mining technology has important stratagem significance. Moving mining robot is the carrier while mining, and its localization accuracy has direct influence on robot＇s control and mining efficiency. An integrated location method based on pseudo long baseline and dead reckoning （PLBL/DR） was proposed, and the Kalman filter structure was established. Considering the complex unknown environment and insufficiently known system state information and an inaccurate priori noise statistics in deep seabed, adaptive Kalman filtering （AKF） algorithm was applied for data fusion and amending filter gain. The feasibility of this method was tested by simulation research results.
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