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INTEGRATED NAVIGATION SYSTEM APPLIED TO DYNAMIC MODELING OF AUTONOMOUS UNDERWATER VEHICLE

机译:集成导航系统在水下自动驾驶汽车动力学建模中的应用

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Autonomous Underwater Veh icle (AUV), a type of UUV, re quires a precise navigation system for loca lization, positioning, path tracking, guidance, and control. In order to develop a robust an d precise AUV navigation system, we need to know an o verall modeling of AUV. AUV Modeling is a complex problem and involves the interdiciplinary study of kinematic, hydrostatics, and hydrodynamics. For instance, an increased knowle dge on hydrodynamicparameters then it leads to a better navigation solution, system design and performance. The overall objective of this paper is to accomplish dynamic mathematical modeling of an AUV and then to develop and implement a low-cost Integrated Navigation System based on error models of In ertial Navigation System (INS) and its aiding devices such as Doppler Velocity Log (DVL), compass, Pressure Depth Sensor. A 20-state INS error model and the corresponding measurement models of those aiding sources will be derived for the KF. The simulation results confirmed that low-cost IMU sensors produce a notable amount of noisy measurements but a KF can effectively mitigate those drawbacks.
机译:自主水下航行器(AUV)是一种UUV,需要精确的导航系统来进行定位,定位,路径跟踪,引导和控制。为了开发强大而精确的AUV导航系统,我们需要了解AUV的总体建模。 AUV建模是一个复杂的问题,涉及运动学,流体静力学和流体动力学的跨学科研究。例如,增加对水动力参数的了解,可以带来更好的导航解决方案,系统设计和性能。本文的总体目标是完成AUV的动态数学建模,然后基于惯性导航系统(INS)的误差模型及其辅助设备(如多普勒速度测井仪( DVL),罗盘,压力深度传感器。将为KF导出20状态INS误差模型和那些辅助源的相应测量模型。仿真结果证实,低成本IMU传感器会产生大量的噪声测量,但KF可以有效地缓解这些缺陷。

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