基于超短基线/多普勒的水下机器人位置估计

为解决深海复杂环境下采用水声定位系统实现水下机器人位置控制所带来的反馈信号延迟问题 ,提出了基于 USBL/Doppler的水下机器人位置估计算法 .文中首先根据导航系统确定卡尔曼滤波器结构并建立了系统的状态方程和观测方程 ,同时 ,为了提高估计精度 ,引入自适应卡尔曼滤波理论 ,以降低系统对环境和初始噪声估计精度的敏感性 .最后通过数字仿真验证了算法的有效性 ,并给出了结论

A Position estimation algorithm for underwater vehicle is proposed based on the USBL/Doppler to cope with position feedback delay due to the underwater acoustic positioning system. The Kalman filter structure with the state equation and observation equation is established according to the navigation system for underwater vehicle. Moreover, the theory of adaptive Kalman filter is incorporated into the algorithm in order to enhance the estimation precision and make the system insensitive to the environment and initial conditions. Simulation result verifies the validity of the algorithm and conclusion is provided at the end of the paper.

中国科学院创新基金资助项目 (资助号 :A0 10 60 3 )