首页> 外文学位 >Decentralized estimation using information consensus filters with a multi-static UAV radar tracking system.
【24h】

Decentralized estimation using information consensus filters with a multi-static UAV radar tracking system.

机译:使用信息共识滤波器和多静态无人机雷达跟踪系统进行分散估计。

获取原文
获取原文并翻译 | 示例

摘要

This dissertation lays out a multi-static radar system with mobile receivers. The transmitter is at a known location emitting a radar signal that bounces off a target. The echo is received by a team of UAVs that are capable of estimating both time-delay and Doppler from the received signal. Several methods for controlling the movement of mobile sensor platforms are presented to improve target tracking performance. Two optimization criteria are derived for the problem, both of which require some type of search procedure to find the desired solution. Simulations are used to show the benefit of using closed-loop sensor control for the special case of an EKF tracking filter. In addition, a simpler closed-form approach based on one of the algorithms is also presented and is shown to have performance similar to that obtained using the optimal algorithms.;To decentralize the estimation in the UAV network, an information consensus filter (ICF) is presented. In the ICF each agent maintains a local estimate, which is shown to be unbiased and conservative with respect to the local covariance matrix estimate. The ICF does not take into account unknown track-to-track correlation that occurs when local independent estimates pass through a common process model. However, it does eliminate the redundancy incurred when communicating information through general network topologies, including graphs containing loops.;In the ICF a discrete-time consensus filter is used to handle the communication of information between nodes (UAVs) in the network. Communication is local in that each agent can only communicate with local neighbors and not the entire network. A second-order discrete-time consensus protocol is developed. Necessary and sufficient conditions are given that ensure the team of agents achieves consensus using the second-order protocol.;Using insights from the analysis of the ICF an extension is made by adding an observation buffer to the ICF. The new filter is called the information consensus filter with an observation buffer (ICFOB). The track-to-track correlation occurring from independent estimates passing through a common process model does not affect the ICFOB as it does other decentralized estimation methods. The ICFOB is shown to be equivalent to a centralized filter that has access to every measurement in a network. There are two caveats to this equivalency. First, at any point in time, the prior ICFOB estimate is equal to the prior centralized filter estimate found by fusing the observations that are taken before those stored in the buffer. The a posteriori estimates using observations in the buffer are not equal to estimates from the centralized filter since the agents have not finished disseminating those observations throughout the sensor network. Second, the ICFOB needs to know the number of active sensors in the network. The number of sensors is global information, therefore, the ICFOB is not fully decentralized. If the number of sensors is not known, the local estimates are conservative.
机译:本文提出了一种带有移动接收机的多静态雷达系统。发射器在已知位置,发射从目标反弹的雷达信号。回声由一组UAV接收,它们能够从接收到的信号中估计时延和多普勒。提出了几种控制移动传感器平台运动的方法,以提高目标跟踪性能。针对该问题导出了两个优化标准,这两个标准都需要某种类型的搜索过程才能找到所需的解决方案。通过仿真显示了在特殊情况下使用EKF跟踪滤波器使用闭环传感器控制的好处。此外,还提出了一种基于其中一种算法的更简单的封闭形式方法,该方法具有与使用最佳算法获得的性能相似的性能。为了在无人机网络中分散估计,信息共识滤波器(ICF)被表达。在ICF中,每个代理都维护一个局部估计,相对于局部协方差矩阵估计,该估计显示为无偏和保守的。 ICF未考虑本地独立估计通过通用过程模型时发生的未知的轨道间关联。但是,它确实消除了通过一般的网络拓扑(包括包含环路的图)进行信息通信时所产生的冗余。在ICF中,离散时间共识过滤器用于处理网络中节点(UAV)之间的信息通信。通信是本地的,因为每个代理只能与本地邻居通信,而不能与整个网络通信。开发了二阶离散时间共识协议。给出了必要条件和充分条件,以确保代理团队使用二阶协议达成共识。;利用对ICF的分析得出的见解,可以通过向ICF添加观察缓冲区来进行扩展。新的过滤器称为带有观察缓冲区(ICFOB)的信息共识过滤器。与通过其他分散式估算方法进行的情况一样,由独立估算通过通用流程模型产生的轨间相关性不会影响ICFOB。所示的ICFOB等效于可访问网络中每个测量值的集中式过滤器。这种等效性有两个警告。首先,在任何时间点,先前的ICFOB估计值等于通过融合在存储在缓冲区中的观察值之前获得的观察值而得出的先前的集中式滤波器估计值。由于代理还没有完成在传感器网络中传播这些观测值,因此使用缓冲区中的观测值进行事后估算不等于来自集中式过滤器的估算值。其次,ICFOB需要知道网络中活动传感器的数量。传感器的数量是全球信息,因此,ICFOB尚未完全分散。如果不知道传感器的数量,则本地估计是保守的。

著录项

  • 作者

    Casbeer, David W.;

  • 作者单位

    Brigham Young University.;

  • 授予单位 Brigham Young University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 140 p.
  • 总页数 140
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

  • 入库时间 2022-08-17 11:37:39

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