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New Algorithms for Designing Unimodular Sequences With Good Correlation Properties

机译:设计具有良好相关性的单模序列的新算法

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摘要

Unimodular (i.e., constant modulus) sequences with good autocorrelation properties are useful in several areas, including communications and radar. The integrated sidelobe level (ISL) of the correlation function is often used to express the goodness of the correlation properties of a given sequence. In this paper, we present several cyclic algorithms for the local minimization of ISL-related metrics. These cyclic algorithms can be initialized with a good existing sequence such as a Golomb sequence, a Frank sequence, or even a (pseudo)random sequence. To illustrate the performance of the proposed algorithms, we present a number of examples, including the design of sequences that have virtually zero autocorrelation sidelobes in a specified lag interval and of long sequences that could hardly be handled by means of other algorithms previously suggested in the literature.
机译:具有良好自相关特性的单模(即恒模)序列在通信和雷达等多个领域都很有用。相关函数的积分旁瓣能级 (ISL) 通常用于表示给定序列的相关属性的优度。在本文中,我们提出了几种用于 ISL 相关指标局部最小化的循环算法。这些循环算法可以使用良好的现有序列进行初始化,例如 Golomb 序列、Frank 序列,甚至是(伪)随机序列。为了说明所提出的算法的性能,我们提出了一些例子,包括设计在指定的滞后区间内自相关旁瓣几乎为零的序列,以及以前在文献中提出的其他算法几乎无法处理的长序列。

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