关键词: 多水下自治机器人, 协同定位, 水声通信延迟, 延时扩展卡尔曼滤波

Abstract:

Considering the positioning failure caused by the communication delay during cooperative location of multiple unmanned underwater vehicles (UUV),  a delayed extended Kalman filter (DEKF) method for localization error correction is proposed which is based on least mean square error of state estimation. Firstly, the system state equation with hydro-acoustic communication delay is established, and the measure equation of multiple UUVs is derived using the system state transition matrix. Then we introduce the extended Kalman filter (EKF) localization algorithm for cooperative location of multiple UUVs considering hydro-acoustic communication delay, and analyze the disadvantages of this method. Finally, on the basis of EKF, through analyzing the influence of measure information delay to state estimation, the equivalent measurement model is established and the DEKF algorithm based on least mean square error of state estimation is designed. The simulation results show that this method can effectively correct localization errors caused by communication delay during the cooperative location, which is of great significance in engineering practice.

Key words: multiple unmanned underwater vehicles (UUV), cooperation location, hydro-acoustic communication delay, delayed extended Kalman filter (DEKF)