공분산 행렬 기반 버스트 신호 블라인드 탐지

초록

Burst signal detection presents significant challenges for non-cooperative contexts, as it should be performed blindly due to absence of prior timing information. Previous study has demonstrated that, at high sampling rates, covariance matrix-based detection achieves superior detection performance compared to energy-based detection for burst signals. This paper proposes a blind burst signal detection algorithm that incorporates covariance matrix-based test statistics, which utilize the correlation among adjacent received samples, with a window segmentation method, and analyzes its detection performance. The proposed method is verified through computer simulations with burst signals of various lengths, symbol rates, and modulation schemes. It is confirmed that, when high sampling rates are ensured, the proposed method provides improved burst signal detection performance.

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