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Radar Based Navigation in Unknown Terrain.

机译:未知地形中基于雷达的导航。

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摘要

There is a great need to develop non-GPS based methods for positioning and navigation in situations where GPS is not available. This research focuses on the development of an Ultra-Wideband Orthogonal Frequency Division Multiplexed (UWB-OFDM) radar as a navigation sensor in GPS-denied environments. A side-looking vehicle-fixed UWB-OFDM radar is mounted to a ground or aerial vehicle continuously collecting data. A set of signal processing algorithms and methods are developed which use the raw radar data to aide in calculating the vehicle position and velocity via a simultaneous localization and mapping (SLAM) approach. The radar processing algorithms detect strong, persistent, and stationary reflectors embedded in the environment and extract range/Doppler measurements to them. If the radar is the only sensor available, the measurements are used to directly compute the vehicle position via an extended Kalman filter (EKF) or Levenberg-Marquardt solver. If an existing navigation platform is available, the measurements are combined with the other sensors in an EKF. The developed algorithms are tested via both a series of airborne simulations and a ground-based experiment. The airborne simulations are performed with simulated commercial-grade, tactical-grade, and navigation-grade INS systems available. The experiment is performed with an indoor mobile platform containing an HG1700 tactical-grade INS and an X-band 500MHz UWB-OFDM radar. For all configurations, the computed navigation solution performance is analyzed with the following sensor availability: radar-only, INS-only, and combined radar/INS. In both simulation and experimental scenarios, the integrated INS/UWB-OFDM system shows significant improvements over an INS-only navigation solution. The radar-only system performs well assuming high availability of reflectors to track, with decreased performance when reflector-less environments are encountered.
机译:迫切需要开发基于GPS的非GPS方法,以在GPS不可用的情况下进行定位和导航。这项研究的重点是在GPS受限环境中作为导航传感器的超宽带正交频分复用(UWB-OFDM)雷达的开发。侧面固定在车辆上的UWB-OFDM雷达安装在连续收集数据的地面或空中车辆上。开发了一组信号处理算法和方法,这些算法和方法使用原始雷达数据通过同时定位和制图(SLAM)方法帮助计算车辆位置和速度。雷达处理算法检测嵌入在环境中的坚固,持久和固定的反射器,并向它们提取距离/多普勒测量值。如果雷达是唯一可用的传感器,则测量值将通过扩展的卡尔曼滤波器(EKF)或Levenberg-Marquardt求解器直接用于计算车辆位置。如果可以使用现有的导航平台,则将测量结果与EKF中的其他传感器合并。所开发的算法通过一系列机载仿真和地面实验进行了测试。机载仿真是使用可用的仿真商业级,战术级和导航级INS系统执行的。该实验是在一个室内移动平台上进行的,该平台包含HG1700战术级INS和X波段500MHz UWB-OFDM雷达。对于所有配置,将通过以下传感器可用性来分析计算出的导航解决方案性能:仅雷达,仅INS和组合式雷达/ INS。在仿真和实验场景中,集成的INS / UWB-OFDM系统都比仅INS的导航解决方案有了显着改进。仅雷达系统假设反射器的跟踪可用性很高,而在遇到无反射器的环境时性能会下降。

著录项

  • 作者

    Kauffman, Kyle J.;

  • 作者单位

    Air Force Institute of Technology.;

  • 授予单位 Air Force Institute of Technology.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 132 p.
  • 总页数 132
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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