首页> 外文会议>2014 Oceans-St. John's Conference >Results from COLLAB13 sea trial on tracking underwater targets with AUVs in bistatic sonar scenarios
【24h】

Results from COLLAB13 sea trial on tracking underwater targets with AUVs in bistatic sonar scenarios

机译:COLLAB13海上试验在双基地声纳场景中使用AUV跟踪水下目标的结果

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

We describe the implementation of a novel non-myopic, receding horizon strategy to control the movement of an AUV towing a line array acting as a receiver node in a multistatic network for littoral surveillance and Anti-Submarine Warfare (ASW). The algorithm computes the vehicle heading angles to minimize the expected target position estimation error of a tracking filter. Minimizing this error is typically of the utmost interest in target state estimation since it is one way of maintaining track. The optimization solves a resulting decision tree taking into consideration a planning future horizon. In this paper, we focus on how to solve the different challenges related to the implementation of this kind of computational intensive algorithms on vehicles operating in realistic ASW scenarios and characterized by limited computational power. Specifically, we describe the multistatic network used in COLLAB13 experiments, how we simplify the solution of the resulting decision tree and the implementation of the algorithm in CMRE's software system running on AUVs and based on MOOS-IvP middleware. We conclude reporting results from COLLAB13 which demonstrate the feasibility to use the proposed algorithm in realistic operations onboard AUVs and its effectiveness over conventional predefined tracklines.
机译:我们描述了一种新型的非近视,后视地平线策略的实现,以控制AUV拖曳作为多站网络用于沿海监视和反潜战争(ASW)的接收器节点的线阵列的运动。该算法计算车辆的转向角以最小化跟踪滤波器的预期目标位置估计误差。在目标状态估计中,最大程度地降低这种误差通常是最重要的,因为这是保持跟踪的一种方法。该优化考虑了计划的未来范围,解决了最终的决策树。在本文中,我们着重于如何解决与在实际ASW场景下运行且计算能力有限的车辆上实施这种计算密集型算法有关的各种挑战。具体来说,我们描述了COLLAB13实验中使用的多静态网络,如何简化结果决策树的解决方案以及在基于AUV并基于MOOS-IvP中间件的CMRE软件系统中算法的实现。我们总结了COLLAB13的报告结果,这些结果表明了在拟议的AUV机上实际操作中使用拟议算法的可行性及其在常规预定义航迹上的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号