无外部信息辅助的主动式声呐时间开窗导航定位模型

Active Sonar Time Window Navigation and Positioning Model Without Appending External Navigation Information

  • 摘要: 受限于海底导航信标时间同步的固有难度,水下导航通常采用主动式定位模型。然而,该模型总是不适定的,即每个观测对应载体信号收发时刻的两个待定点。忽略载体运动,可取 0.5 倍的信号往返程传播时间作为观测值进行定位,但这必然引入模型误差,特别是深海场景或载体高速运动情形。若使用多普勒测速或惯导等航位推算信息,则会导致声呐导航依存于外部信息。对此, 本文提出了一种附加载体运动学参数的主动式声呐时间开窗导航定位模型,实现了载体位置、速度、加速度等信息的联合估计, 在实时输出载体当前时刻坐标信息的同时, 实现了载体任意时刻运动状态信息的获取,解决了主动式定位模型的不适定性问题;同时,提出了时间开窗导航定位精度几何因子(TRDOP), 以评估时间开窗导航定位构型强度。研究表明, TRDOP 可很好刻画时间开窗导航定位构型优劣,且时间开窗导航定位模型显著优于传统空间交会定位模型。在日本公开数据集上的测试结果显示, 主动式声呐时间开窗导航定位模型的导航定位精度优于 5m,且窗口中间时刻定位精度更高。

     

    Abstract: Objectives: Due to the inherent difficulty of time synchronization of submarine navigation beacons, underwater navigation usually adopts an active positioning model. However, the model is always ill-defined, that is, each observation corresponds to two waiting points at which the carrier signal is sent and received. When the carrier motion is ignored, half of the signal round-trip travel time can be used as the observed value to locate the signal, but this will inevitably introduce model errors, especially in deepsea scenes or high-speed carrier motion. If the use of Doppler velocity measurement or inertial navigation and other dead reckoning information, it will lead to sonar navigation dependent on external information, but no longer independent. Methods: In this paper, a time-window navigation and positioning model with additional carrier kinematic parameters is proposed to realize the joint estimation of carrier position, velocity, acceleration and other information, which can not only output the carrier's current moment coordinates, but also obtain the carrier's motion information at any time, such as the carrier's position, velocity and acceleration at the middle of the window. Results: The problem of the inadequacy of the active positioning model is solved effectively. At the same time, the concept of geometric factor (KDOP) is proposed to evaluate the geometric strength of time-windowed navigation. The results show that the KDOP proposed in this paper can well describe the advantages and disadvantages of the time-windowed navigation and positioning configuration, and the time-windowed navigation and positioning model is significantly superior to the traditional spatial intersection positioning model. Conclusions: The test results on the Japanese public data set show that the navigation and positioning accuracy proposed in this paper is better than 5m, and the positioning accuracy at the middle time of the window is higher.

     

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