PN code acquisition using signed-rank-based nonparametric detectors in DS/SS systems

Kim, Hong Gil; Song, Iickho; Yoon, Seokho; Kim, Sun Yong

doi:10.1109/25.938589

Cited by 7 publications

References 12 publications

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Permutation tests for nonparametric detection

2012

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In this paper, the authors provide a methodology to design nonparametric permutation tests and, in particular, nonparametric rank tests for applications in detection. In the first part of the paper, the authors develop the optimization theory of both permutation and rank tests in the Neyman-Pearson sense; in the second part of the paper, they carry out a comparative performance analysis of the permutation and rank tests (detectors) against the parametric ones in radar applications.First, a brief review of some contributions on nonparametric tests is realized. Then, the optimum permutation and rank tests are derived. Finally, a performance analysis is realized by Monte-Carlo simulations for the corresponding detectors, and the results are shown in curves of detection probability versus signal-to-noise ratio.

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Permutation tests for nonparametric detection

2012

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DS/SS code acquisition using a locally suboptimum rank detector

Kim¹,

Jung²,

Song³

et al.

MILCOM 2000 Proceedings. 21st Century Military Communications. Architectures and Technologies for Information Superiority (Cat.

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In this paper, signed-rank based nonparametric detectors are used forpseudonoise (PN) code acquisition in direct sequence spread spectrum (DS/SS) systems. We first derive the locally optimum rank (LOR) detector, and then propose a locally suboptimum rank (LSR) detector and a modijied signed-rank (MSR) detector using approximate score functions. We compare the single-dwell scheme without the ver-$cation mode using the proposed LSR and MSR detectors with that using the conventional squared-sum (SS) and mod-$ed sign (MS) detectors. From the simulation results, it isshown that the proposed LSR and MSR detectors pe$orm better than the MS detector by about 2 -3dB and are nearly optimum.

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