基于能量块与峰度特征的联合检测算法研究
Study on the joint detection algorithm based on energy block and kurtosis characteristic
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摘要: 为提高信号检测概率,提出了基于归一化峰度的特征检测与能量块检测相结合的联合检测算法:在信号和噪声均服从高斯分布时,采用能量块检测的相关计算公式;对数据块中信号点个数远小于数据块长度时,采用数学方法分析归一化峰度值的变化情况.仿真结果表明,联合检测方法提高了检测概率和检测性能,具有一定的应用价值.Abstract: A joint detection algorithm was presented based on characteristic detection of normalized kurtosis and energy block detection to improve the detection probability.When signal and noise are Gaussian distribution,the related calculation formula was applied for the energy block detection.Normalized kurtosis variation was analyzed based on mathematic theory when the number of signals changes from small to maximum in the data block.The simulation results showed that the detection probability and detection performace were improved by using the joint detection algorithm,so it will be useful in the detection of data block.
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Key words:
- normalized kurtosis /
- energy block detection /
- characteristic detection /
- joint detection
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