一种基于双模型的低成本多AUV协同定位方法

Low-cost multi-AUV cooperative localization method based on dual-model

  • 摘要:
      目的  针对多自主水下航行器(AUV)上装备的惯性导航系统(INS)和多普勒速度计程仪(DVL)失效或未配备的情况,结合传统的扩展卡尔曼滤波(EKF)估计,提出一种基于双模型的协同定位方法。
      方法  建立相对运动模型和双领航状态空间模型,通过水声通信,利用相对运动模型估计跟随AUV的速度信息,再应用双领航模式的多AUV协同定位状态空间模型,进一步提高协同定位系统的鲁棒性和准确性,利用海试数据进行半实物仿真验证。
      结果  结果表明,基于双模型的主从式多AUV协同定位方法,能够在跟随AUV上没有INS和DVL的情况下,实时估计跟随AUV的位置。
      结论  该方法能够保障协同定位系统定位精度在允许的范围内,降低多AUV协同定位系统的成本。

     

    Abstract:
      Objectives  In order to solve the problem of inertial navigation systems(INS)and doppler velocity logs(DVL) on multiple autonomous underwater vehicles(AUV) failing or having no sensors, combined with the traditional extended Kalman filter estimation, a cooperative positioning method based on dual-model is proposed.
      Methods  A relative motion model and two-leader state space model are established. The velocity information of the following AUV is estimated using the relative motion model in underwater acoustic communication, and then the multi-AUV coordinated positioning state space model with the two-leader model is applied to further improve the robustness and accuracy of the coordinated positioning system. Semi-real simulation experiments are then carried out using sea test data.
      Results  The results show that the leader-follower multi-AUV cooperative localization method based on the dual-model can estimate the position of the following AUV in real time without INS or DVL on the AUV.
      Conclusions  This method can ensure that the positioning accuracy of the cooperative localization system is within the allowable range, and reduce the cost of the multi-AUV cooperative localization system.

     

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