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Phase Code Discovery for Pulse Compression Radar: A Genetic Algorithm Approach

Authors :
Xie, Xinyan
Zhang, Runxin
Shao, Yulin
Lu, Lu
Publication Year :
2022

Abstract

Discovering sequences with desired properties has long been an interesting intellectual pursuit. In pulse compression radar (PCR), discovering phase codes with low aperiodic autocorrelations is essential for a good estimation performance. The design of phase code, however, is mathematically non-trivial as the aperiodic autocorrelation properties of a sequence are intractable to characterize. In this paper, we put forth a genetic algorithm (GA) approach to discover new phase codes for PCR with the mismatched filter (MMF) receiver. The developed GA, dubbed GASeq, discovers better phase codes than the state of the art. At a code length of 59, the sequence discovered by GASeq achieves a signal-to-clutter ratio (SCR) of 50.84, while the best-known sequence has an SCR of 45.16. In addition, the efficiency and scalability of GASeq enable us to search phase codes with a longer code length, which thwarts existing deep learning-based approaches. At a code length of 100, the best phase code discovered by GASeq exhibit an SCR of 63.23.<br />Comment: Keywords: Genetic algorithm, pulse compression radar, phase code, mismatched receiver, signal-to-clutter ratio

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2207.14631
Document Type :
Working Paper