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Modern Methods of Radar Data Extraction and Track Management Systems

机译:现代雷达数据提取和轨道管理系统方法

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First we give an overview of the content of a dighalized target plot and the conflicting requirements of a track management system. This should find a reasonable compromise since a bijective plot-track-assignment does not exist. After this overview we discuss the new methods of radar data extraction that we have examined. We have studied the effectiveness of image processing algorithms and track before detect methods for plot formation. The latter have only been used up to now for offline evaluation because of the increased calculation time. In the development of multi-hypothesis tracking (MHT) we had several different approaches: We had to distinguish between the track initialization and firm track phases, have separated the two phases and developed an MHT for track initialization. We have also implemented an MHT for the firm track phase without cluster hypothesis in SDF (Sensor Data Fusion) in the F124 project. We have considered implementing an MHT with cluster hypothesis in our ADA software and have built demonstrators in ADA95 and in Java. Additional we have applied for a patent for a fully automatic sensor misalignment correction method which is able to correct misalignments of sensors in azimuth and range, and slowly changing systematic errors (bias). In the last section, conclusions, we give an overview of our future activities.
机译:首先,我们概述了无限的目标图的内容以及轨道管理系统的冲突要求。这应该找到合理的折衷,因为轨迹分配不存在。在此概述之后,我们讨论了我们检查过的雷达数据提取的新方法。我们已经研究了图像处理算法和轨道在绘制地层形成方法之前的有效性。由于计算时间增加,后者仅用于离线评估。在多假设跟踪(MHT)的开发中,我们有几种不同的方法:我们必须区分轨道初始化和坚实的轨道阶段,分离了两个阶段并开发了MHT进行轨道初始化。我们还为F124项目中的SDF(传感器数据融合)中没有集群假设的坚实轨道阶段,我们也为MHT实施了MHT。我们已经考虑在我们的ADA软件中实施了MHT,并在我们的ADA 95和Java中建立了示威者。其他我们申请了一种全自动传感器未对准校正方法的专利,该校正方法能够纠正方位角和范围内传感器的错位,以及缓慢改变系统错误(偏置)。在最后一节中,结论,我们概述了我们未来的活动。

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