Terrain Aided Navigation for Long Range AUV operations at arctic latitudes

G. Salavasidis, C. Harris, S. McPhail, A. Phillips, E. Rogers
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引用次数: 23

Abstract

This paper investigates the potential of use of Terrain Aided Navigation (TAN) methods to exploit the extended endurance capabilities of an enhanced 1500m depth rated variant of the Autosub Long Range (ALR), the ALR1500 Autonomous Underwater Vehicle (AUV), for operations under the Arctic ice. A simulator for the TAN system using a low resolution Arctic bathymetric map is developed to study the capability to reduce/bound the positioning error growth due to the Dead Reckoning (DR) drift over time. Bathymetric measurements are obtained using a low sample rated single beam echo sounder and a Jittered Bootsrap Particle Filter (JBPF) is used for the multi-sensor data fusion problem. Sensitivity analysis of JBPF has been performed for a range of values of number of particles, jittering variances and measurement frequencies and a discussion over the results is given. Results from the simulation demonstrate that JBPF is capable of providing a robust and accurate solution to the localization problem provided that the AUV follows a trajectory with a sufficiently variant terrain. Finally, a brief discussion regarding the future extension of this work is also provided.
北极地区远程水下航行器操作的地形辅助导航
本文研究了使用地形辅助导航(TAN)方法的潜力,以利用Autosub Long Range (ALR)的增强型1500米深度额定变体ALR1500自主水下航行器(AUV)的扩展续航力,用于北极冰层下的作业。开发了一个使用低分辨率北极水深图的TAN系统模拟器,以研究减少/限制由于航位推算(DR)随时间漂移而导致的定位误差增长的能力。采用低采样率单波束测深仪获得测深数据,采用抖动引导粒子滤波器(JBPF)进行多传感器数据融合。对JBPF在粒子数、抖动方差和测量频率范围内的灵敏度进行了分析,并对结果进行了讨论。仿真结果表明,当水下机器人的轨迹具有足够的地形变化时,JBPF能够提供鲁棒性和准确性的定位问题解决方案。最后,对今后的扩展工作进行了简要的讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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