【摘要】 该文研究了配置高度计和深度计的水下机器人海底地形跟踪的问题。采用扩展卡尔曼滤波对高度计和深度计数据进行数据融合,提高了AUV对海底高度信息感知的能力,通过最小二乘法对海底地形坡度进行估计,预测海底地形变化趋势,提高了水下机器人对海底地形跟踪的能力。最后,通过Matlab仿真对海底地形跟踪算法进行了验证,实验结果表明该文提出的方法是有效的。更多还原

【Abstract】 This paper studied the problem of undersea bottom-following through using the autonomous underwater vehicle(AUV)equipped with altimeter and depth gauge. We can improve the ability of AUV to perceive the information of the seabed by using the extended kalman filter(EKF) to complete the information fusion of data come from altimeter and depth gauge. The seabed terrain slope is estimated by the least square method and then the trend of the seabed terrain can be predicted,which improve the ability of the AUV to track the seabed terrain. In the end,the seabed terrain tracking algorithm was verified by Matlab simulation,and the experimental results showed that the proposed method was effective.更多还原