西南科技大学学报
西南科技大學學報
서남과기대학학보
JOURNAL OF SOUTHWEST CHINA INSTITUTE OF TECHNOLOGY
2011年
4期
71-74
,共4页
调制识别%高阶累积量%相位差分%决策分类
調製識彆%高階纍積量%相位差分%決策分類
조제식별%고계루적량%상위차분%결책분류
Modulation classification%Higher-order cumulants%Phase difference%Decision-tree classification
针对BPSK，QPSK，OQPSK和8PSK信号的调制模式自动识别，传统的基于高阶累积量算法无法区分QPSK和OQPSK，因此提出了一种基于差分高阶累积量的识别算法。该算法首先用四阶累积量提取待识别信号和其差分序列的特征参数，然后用决策树分类法实现信号的分级识别。理论分析和计算机仿真结果表明该算法有较强的抗噪声和抗相位抖动能力，在信噪比〉3dB时识别率达95％以上，更适用于较低信噪比下信号的识别。
針對BPSK，QPSK，OQPSK和8PSK信號的調製模式自動識彆，傳統的基于高階纍積量算法無法區分QPSK和OQPSK，因此提齣瞭一種基于差分高階纍積量的識彆算法。該算法首先用四階纍積量提取待識彆信號和其差分序列的特徵參數，然後用決策樹分類法實現信號的分級識彆。理論分析和計算機倣真結果錶明該算法有較彊的抗譟聲和抗相位抖動能力，在信譟比〉3dB時識彆率達95％以上，更適用于較低信譟比下信號的識彆。
침대BPSK，QPSK，OQPSK화8PSK신호적조제모식자동식별，전통적기우고계루적량산법무법구분QPSK화OQPSK，인차제출료일충기우차분고계루적량적식별산법。해산법수선용사계루적량제취대식별신호화기차분서렬적특정삼수，연후용결책수분류법실현신호적분급식별。이론분석화계산궤방진결과표명해산법유교강적항조성화항상위두동능력，재신조비〉3dB시식별솔체95％이상，경괄용우교저신조비하신호적식별。
A new method based on feature extraction was proposed for the recognition of M-ary Phase Shift Keying （MPSK） signals. As features, fourth order cumulants of the input samples and phase differential sequences were applied, and classifier based on decision tree was used. Theoretical arguments were verified via extensive simulations. It is shown that the cumulant-based features have robust anti-noise and an- ti-phase jitter ability. Simulation results demonstrate that the correct classification probability （Pcc） with the proposed algorithm is above 95% when signal-to-noise （SNR） 〉 3 dB, thus this method is more suitable for the identification of MPSK signals at low SNR situation.
