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MDL approach for multiple low observable track initiation

机译：MDL方法可用于多个低可观察轨道起始

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摘要

In this paper the track initiation problem is formulated as multiple composite hypothesis testing using maximum likelihood estimation with probabilistic data association (ML-PDA). The hypothesis selection is based on the minimum description length (MDL) criterion. We first review some well-known approaches for statistical model selection and the advantage of the MDL criterion. Then we present one-dimensional examples to illustrate the MDL criterion used in multiple composite hypothesis testing and the performance limit of the ML-PDA for track initiation is interpreted in terms of the sharpness of the hypothesis testing. Finally, we apply the MDL approach for the detection and initiation of tracks of incoming tactical ballistic missiles in the exo-atmospheric phase using a surface-based electronically scanned array (ESA) radar. The targets are characterized by low signal-to-noise ratio (SNR), which leads to low detection probability and high false alarm rate. The target acquisition problem is formulated using a batch of radar scans to detect the presence of up to two targets. The ML-PDA estimator is used to initiate the tracks assuming the target trajectories follow a deterministic state propagation. The approximate MDL criterion is used to determine the number of valid tracks in a surveillance region. The detector and estimator are shown to be effective even at 4.4 dB average SNR.
机译：在本文中，使用最大概率估计和概率数据关联（ML-PDA）将轨迹起始问题表述为多重复合假设测试。假设选择基于最小描述长度（MDL）标准。我们首先回顾一些著名的统计模型选择方法以及MDL标准的优势。然后，我们提供一维示例，以说明在多个复合假设测试中使用的MDL准则，并根据假设测试的清晰度来解释ML-PDA用于轨迹启动的性能极限。最后，我们使用基于表面的电子扫描阵列（ESA）雷达，将MDL方法应用于在大气外阶段探测和启动进入战术弹道导弹的航迹。目标的特征在于低信噪比（SNR），从而导致低检测概率和高虚警率。使用一批雷达扫描来检测多达两个目标的存在，从而制定了目标获取问题。假设目标轨迹遵循确定性状态传播，则ML-PDA估计器用于启动轨迹。近似的MDL标准用于确定监视区域中有效磁道的数量。示出了检测器和估计器即使在4.4 dB的平均SNR时也有效。

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