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Construction of Multi-Dimensional Periodic Complementary Array Sets

机译:多维周期互补阵列集的构建

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摘要

Multi-dimensional (MD) periodic complementary array sets (CASs) with impulse-like MD periodic autocorrelation function are naturally generalized to (one dimensional) periodic complementary sequence sets, and such array sets are widely applied to communication, radar, sonar, coded aperture imaging, and so forth. In this letter, based on multi-dimensional perfect arrays (MD PAs), a method for constructing MD periodic CASs is presented, which is carried out by sampling MD PAs. It is particularly worth mentioning that the numbers and sizes of sub-arrays in the proposed MD periodic CASs can be freely changed within the range of possibilities. In particular, for arbitrarily given positive integers M and L, two-dimensional periodic polyphase CASs with the number M~2 and size L × L of sub-arrays can be produced by the proposed method. And analogously, pseudo-random MD periodic CASs can be given when pseudorandom MD arrays are sampled. Finally, the proposed method's validity is made sure by a given example.
机译:具有脉冲类MD周期自相关函数的多维(MD)周期互补阵列集(CASs)自然被推广为(一维)周期互补序列集,并广泛应用于通信、雷达、声纳、编码孔径成像等领域。本文基于多维完美阵列(MD PAs),提出了一种通过对MD PAs进行采样来构建MD周期性CAS的方法。特别值得一提的是,所提出的MD周期性CAS中子阵列的数量和大小可以在各种可能性范围内自由变化。特别是,对于任意给定的正整数M和L,所提方法可以产生子阵列数量为M~2、大小为L×L的二维周期性多相CAS。类似地,当对伪随机 MD 阵列进行采样时,可以给出伪随机 MD 周期性 CAS。最后,通过给定的实例确保了所提方法的有效性。

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