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On model, algorithms and experiment for micro-doppler based recognition of ballistic targets

机译:基于微多普勒的弹道目标识别模型,算法和实验

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摘要

The ability to discriminate between Ballistic Missile warheads and confusing objects is an important topic from different points of view. In particular, the high cost of the interceptors with respect to tactical missiles may lead to an ammunition problem. Moreover, since the time interval in which the defence system can intercept the missile is very short with respect to target velocities, it is fundamental to minimise the number of shoots per kill. For this reason a reliable technique to classify warheads and confusing objects is required. In the efficient warhead classification system presented in this paper a model and a robust framework is developed, which incorporates different microDoppler based classification techniques. The reliability of the proposed framework is tested on both simulated and real data
机译:从不同的角度来看,区分弹道导弹弹头和令人困惑的物体的能力是一个重要的话题。特别是,拦截器在战术导弹方面的高昂成本可能导致弹药问题。此外,由于防御系统可以拦截导弹的时间间隔相对于目标速度而言非常短,因此将每次击杀的发芽数量降至最低至关重要。因此,需要一种可靠的技术来对弹头和混乱的物体进行分类。在本文介绍的高效弹头分类系统中,开发了模型和鲁棒性框架,其中结合了基于微多普勒的不同分类技术。所提出框架的可靠性已在模拟和真实数据上进行了测试

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