In this article, we present an algorithm for the discrimination of the target of interest for the purpose of interdiction in the presence of several spurious targets that are intended to confuse the intercept decision. This is applied to an IR (infrared) detection-based tracking system on a low earth orbit (LEO) satellite and an optical sensor-based tracking system on an interceptor. The spurious targets are released from the target of interest and they move forward at the same speed as the target of interest. They separate due to a release velocity orthogonal to the forward motion. The spurious targets have no distinguishable features so they “look” the same as the target of interest for the sensor. The observations are noisy and unresolved if the distance between these objects is below the sensor resolution threshold, which degrades the performance of the traditional track-to-measurement association method yielding unreliable results. We analyze the history of the track kinematics as well as the trajectory evolution and associate track segments before and after the spurious target separations to select the track of interest from the other spurious tracks in its vicinity. The novelty of the present work is in generalizing the track segment association to a multitarget environment while accounting for unresolved measurements with a physics-based model. This is accomplished via hypothesis testing to find out which of the tracks after the release corresponds to the track before the release, i.e., which is the target to be interdicted. Also, estimation of the separation times is a novelty—it needs the association based on the finite resolution model because the objects are unresolved after separation for some time. It is shown in the simulations that using the track segment association technique, the percentage of correct target selections has been improved to 95% from 55% for the interceptor scenario and from 85% for the LEO scenario, respectively.

中文翻译：

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使用单个无源传感器进行拦截目标选择中的跟踪段关联


在本文中，我们提出了一种算法，用于区分感兴趣的目标，以便在存在多个旨在混淆拦截决策的虚假目标的情况下进行拦截。这适用于低地球轨道 (LEO) 卫星上基于 IR（红外）检测的跟踪系统和拦截器上基于光学传感器的跟踪系统。虚假目标从感兴趣的目标中释放出来，并以与感兴趣的目标相同的速度向前移动。它们由于与向前运动正交的释放速度而分离。虚假目标没有可区分的特征，因此它们“看起来”与传感器感兴趣的目标相同。如果这些物体之间的距离低于传感器分辨率阈值，则观测结果是有噪声且无法解析的，这会降低传统轨迹与测量关联方法的性能，从而产生不可靠的结果。我们分析了轨道运动学的历史以及轨迹演化，并在虚假目标分离之前和之后关联轨道段，以从其附近的其他虚假轨道中选择感兴趣的轨道。目前工作的新颖之处在于将轨道段关联推广到多目标环境，同时使用基于物理的模型解释未解决的测量。这是通过假设检验来找出发行后的哪些曲目与发行前的曲目相对应，即哪个是要拦截的目标来完成的。此外，分离时间的估计也是一个新颖之处——它需要基于有限分辨率模型的关联，因为对象在分离一段时间后仍未解析。 模拟结果表明，使用航迹段关联技术，正确目标选择的百分比已分别从拦截机场景的 55% 和 LEO 场景的 85% 提高到 95%。