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Track-before-detect for multiframe detection with censored observations

机译:检测前跟踪用于带删失观测的多帧检测

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摘要

In this work, we address the problem of target detection from multiple noisy observations produced by a generic sensor. A two-step approach is considered, wherein a censoring stage retains the significant measurements (i.e., those whose likelihood ratio exceeds a primary threshold) in each frame, while a multiframe detector elaborates the preprocessed observations and takes the final decision through a generalized likelihood ratio test. A dynamic programming algorithm to form the decision statistic, which exploits the sparse nature of the censored observations, is proposed. A closed-form complexity analysis is provided, and a thorough performance assessment is undertaken to elicit the tradeoffs among censoring level, system complexity, and achievable performance.
机译:在这项工作中,我们从通用传感器产生的多个嘈杂观测中解决了目标检测的问题。考虑了两步方法,其中检查阶段在每个帧中保留重要的测量值(即那些似然比超过主要阈值的测量),而多帧检测器则对预处理的观测值进行细化并通过广义似然比来做出最终决定测试。提出了一种动态规划算法来形成决策统计量,该算法利用了被检查观测值的稀疏性。提供了一种封闭形式的复杂性分析,并进行了全面的性能评估,以得出检查级别,系统复杂性和可实现的性能之间的折衷。

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