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Ground moving target tracking with space-time adaptive radar

机译:时空自适应雷达对地面运动目标的跟踪

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摘要

Ground moving target tracking by airborne radar provides situational awareness of vehicle movements in the supervised region. Vehicles are detected by applying space time adaptive processing to the received multi channel radar data. The detections are then fed to a tracking algorithm that processes them to tracks. In literature, radar signal processing and ground target tracking are treated as two separate topics and results are not validated by experimental data. The first objective of this thesis is to provide a closer link between these fields. The second objective is to show that tracking performance can be improved by providing additional data from the radar signal processing to the tracking step. The third objective is to validate the algorithm and the performance improvement using experimental data. As a result this thesis presents a unified treatment of ground moving target tracking from radar raw data to established tracks. A complete reference algorithm for ground moving target tracking based on the Gaussian mixture probability hypothesis density filter is presented. In particular, Jacobians of the observation process are derived. They are presented in such a form that immediate implementation in a programming language is possible. In the course of this thesis a measurement campaign with the experimental radar PAMIR of Fraunhofer FHR was conducted. The experiment included two GPS equipped reference vehicles and a multitude of targets of opportunity. Tracking results obtained with this experimental data and the reference tracking algorithm of this thesis are shown. The thesis also enhances the reference target tracking algorithm by a parameter that characterizes the variance of the direction of arrival measurement of the target signal. This parameter is determined adaptively depending on the estimated signal strength and the clutter background. The major contribution with regard to this enhancement is a thorough experimental validation: Firstly, a comparison between GPS based measurements and radar based measurements of the direction of arrival shows that this variance captures the distribution of measurement errors excellently. Secondly, tracking results are compared to the GPS tracks of the ground truth vehicles. It is found that the enhanced algorithm yields superior track quality with respect to both track accuracy and track continuity.
机译:机载雷达对地面移动目标的跟踪提供了在监管区域内车辆运动的态势感知。通过对接收到的多通道雷达数据进行时空自适应处理来检测车辆。然后将检测结果提供给跟踪算法,该算法将其处理为跟踪。在文献中,雷达信号处理和地面目标跟踪被视为两个单独的主题,并且未通过实验数据验证结果。本文的首要目的是在这些领域之间提供更紧密的联系。第二个目的是表明可以通过提供从雷达信号处理到跟踪步骤的其他数据来改善跟踪性能。第三个目标是使用实验数据验证算法和性能改进。结果,本文提出了对地面移动目标跟踪的统一处理,从雷达原始数据到已建立的跟踪。提出了一种基于高斯混合概率假设密度滤波器的地面运动目标跟踪的完整参考算法。特别是推导了观察过程的雅可比行列式。它们以这样的形式呈现:可以用编程语言立即实现。在本文的过程中,进行了弗劳恩霍夫FHR实验雷达PAMIR的测量运动。该实验包括两辆配备GPS的参考车辆和多个机会目标。给出了利用该实验数据获得的跟踪结果以及本文的参考跟踪算法。本文还通过表征目标信号到达方向测量方差的参数增强了参考目标跟踪算法。该参数根据估计的信号强度和杂波背景来自适应确定。关于此增强功能的主要贡献在于进行了全面的实验验证:首先,将基于GPS的测量结果与基于雷达的到达方向测量结果进行比较表明,这种差异很好地捕获了测量误差的分布。其次,将跟踪结果与地面真车的GPS跟踪进行比较。发现增强的算法在轨道精度和轨道连续性方面产生了优良的轨道质量。

著录项

  • 作者

    Kohlleppel Robert;

  • 作者单位
  • 年度 2015
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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