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Real-time observability of targets with constrained processingpower

机译:处理能力受限的目标的实时观测

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This paper discusses an issue in the implementation of Kalman filter tracking systems. The issue is the relationship between processing time in generating measurement data, the search area needed for such measurements, and the errors in the measurement data produced. A key observation is that in certain cases (particularly when the underlying model used in the Kalman filter is not asymptotically stable) processing time may be a very real issue. The analysis of several cases shows that a variable precision measurement computation strategy may be of benefit. One of the motivating examples is a tracking system using image-type data. The study is performed for a first-order system and shows the difficulties encountered with multidimensional systems
机译:本文讨论了卡尔曼滤波器跟踪系统实施中的问题。问题在于生成测量数据的处理时间,进行此类测量所需的搜索区域以及所生成的测量数据中的错误之间的关系。一个关键的观察结果是,在某些情况下(尤其是当卡尔曼滤波器中使用的基础模型不是渐近稳定时),处理时间可能是一个非常现实的问题。对几种情况的分析表明,可变精度测量计算策略可能是有益的。激励示例之一是使用图像类型数据的跟踪系​​统。该研究是针对一阶系统执行的,显示了多维系统遇到的困难

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