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MDL approach for multiple low observable track initiation

机译：MDL方法对于多个低可观察轨道启动

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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，轨道启动问题配制为使用具有概率数据关联（ML-PDA）的最大似然估计的多个复合假设测试。假设选择基于最小描述长度（MDL）标准。我们首先审查一些众所周知的统计模型选择方法以及MDL标准的优势。然后，我们提出一维例子以说明多个复合假说测试中使用的MDL标准，并且在假设检测的锐度方面解释了用于轨道发起的ML-PDA的性能极限。最后，我们使用基于表面的电子扫描阵列（ESA）雷达来应用用于检测和启动EXO-amo-阶段的传入战术弹道导道轨道的MDL方法。目标的特征在于低信噪比（SNR），这导致低检测概率和高误报率。使用批量雷达扫描制定目标采集问题，以检测最多两个目标的存在。 ML-PDA估计器用于发起假设目标轨迹遵循确定性状态传播的轨道。近似MDL标准用于确定监视区域中的有效轨道的数量。探测器和估计器即使在4.4 dB平均SNR中也会有效。

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