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A statistical approach to the optimization of the radar ambiguity function and the chaos-based waveform design

机译:雷达模糊函数优化的统计方法和基于混沌的波形设计

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In this paper we adopt a statistical approach to optimize the ambiguity function of a radar system. By considering the codes defining the transmitted waveform as realizations of a random variable we firstly show that a suitable distribution of the random variable allows to obtain good codes. Secondly we show that using the chaotic skew tent map it is possible to generate deterministic codes having the desired statistical properties. This allows to obtain an optimized global ambiguity function of the radar system. The advantage of using chaos-based sequences is that they can be easily generated in any length and number. We further improve their performance by introducing down sampling. It appears that the proposed sequences have performance quite similar to those of the sequences of the literature computationally optimized.
机译:在本文中,我们采用统计方法来优化雷达系统的歧义功能。通过考虑定义传输波形作为随机变量的实现的代码,我们首先显示随机变量的合适分布允许获得良好的代码。其次,我们示出了使用混沌偏斜帐篷图,可以生成具有所需统计特性的确定性码。这允许获得雷达系统的优化全局模糊功能。使用基于混沌的序列的优点是它们可以在任何长度和数量中容易地产生。我们通过引入抽样进一步提高其性能。似乎所提出的序列具有与计算方式优化的文献序列非常相似的性能。

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