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Group state estimation algorithm using Foliage Penetration GMTI radar detections

机译:基于叶面穿透GMTI雷达检测的群状态估计算法

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This paper describes an algorithm for integrating detections from Foliage Penetrating (FOPEN) Ground Moving Target Indicator (GMTI) radar, to recognize groups of dismounts moving through dense foliage, and to estimate the group states, including the group sizes and the directions of their movements. Difficulties of processing FOPEN GMTI radar detections are best characterized as low target-state-dependent detection probabilities and high non-uniform persistent false alarm densities. To overcome these difficulties, we use the Sum-of-Gaussian (SOG) or Gaussian-Mixture (GM) Cardinalized Probability Hypothesis Density (CPHD) method to detect and track individual dismounts, and then, apply a group dynamics recognition method to the CPHD outputs to recognize the formation and the behavior of the dismounts groups.
机译:本文介绍了一种算法,该算法用于集成从植物穿透力(FOPEN)地面移动目标指示器(GMTI)雷达中检测到的信息,以识别穿过茂密树叶移动的下马群,并估计组状态,包括组大小及其运动方向。 FOPEN GMTI雷达检测的处理难度最好表现为低目标状态相关检测概率和高非均匀持续误报密度。为了克服这些困难,我们使用高斯总和(SOG)或高斯混合(GM)基数化概率假设密度(CPHD)方法来检测和跟踪单个下马,然后将组动力学识别方法应用于CPHD输出以识别下马组的形成和行为。

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