The Hanning self-convolution window (HSCW) is proposed in this paper. And the phase difference correction algorithm based on the discrete spectrum and the HSCW is given. The HSCW has a low peak side lobe level, a high...The Hanning self-convolution window (HSCW) is proposed in this paper. And the phase difference correction algorithm based on the discrete spectrum and the HSCW is given. The HSCW has a low peak side lobe level, a high side lobe roll-off rate, and a simple spectrum representation. Hence, leakage errors and harmonic interferences can be considerably reduced by weighting samples with the HSCW, the parameter estimation by the HSCW-based phase difference correction algorithm is free of solving high order equations, and the overall method can be easily implemented in embedded systems. Simulation and application results show that the HSCW-based phase difference correction algorithm can suppress the impacts of fundamental frequency fluctuation and white noise on harmonic parameter estimation, and the HSCW is advantageous over existing combined cosine windows in terms of harmonic analysis performance.展开更多
针对二次调频-伪码调相(quadratic frequency modulated-pseudo random binary phase code,QFM-PRBC)复合信号伪码估计的难题,提出一种基于分数阶模糊函数(fractional ambiguity function,Fr-AF)和改进的三角窗抗干扰核函数(reduced int...针对二次调频-伪码调相(quadratic frequency modulated-pseudo random binary phase code,QFM-PRBC)复合信号伪码估计的难题,提出一种基于分数阶模糊函数(fractional ambiguity function,Fr-AF)和改进的三角窗抗干扰核函数(reduced interference distribution kernel based on the triangular window,RIDT)变换的伪码估计算法。应用平方法解决伪码与信息码相位突变问题,并用累加平均减小平方法带来的噪声影响,利用分数阶模糊函数估计平方累加后信号的最高项和次高项系数,重构信号对接收端信号降阶;采用奇异值分解(singular value decomposition,SVD)对基于三角窗减少干扰的核函数变换加以改进以提取降阶后信号的伪码序列。仿真实验表明了算法的有效性,当累加次数为20且信噪比在-4 d B以上时,伪码可以正确估计。展开更多
基金Supported by the National Natural Science Foundation of China (Grant No.60872128)
文摘The Hanning self-convolution window (HSCW) is proposed in this paper. And the phase difference correction algorithm based on the discrete spectrum and the HSCW is given. The HSCW has a low peak side lobe level, a high side lobe roll-off rate, and a simple spectrum representation. Hence, leakage errors and harmonic interferences can be considerably reduced by weighting samples with the HSCW, the parameter estimation by the HSCW-based phase difference correction algorithm is free of solving high order equations, and the overall method can be easily implemented in embedded systems. Simulation and application results show that the HSCW-based phase difference correction algorithm can suppress the impacts of fundamental frequency fluctuation and white noise on harmonic parameter estimation, and the HSCW is advantageous over existing combined cosine windows in terms of harmonic analysis performance.
文摘针对二次调频-伪码调相(quadratic frequency modulated-pseudo random binary phase code,QFM-PRBC)复合信号伪码估计的难题,提出一种基于分数阶模糊函数(fractional ambiguity function,Fr-AF)和改进的三角窗抗干扰核函数(reduced interference distribution kernel based on the triangular window,RIDT)变换的伪码估计算法。应用平方法解决伪码与信息码相位突变问题,并用累加平均减小平方法带来的噪声影响,利用分数阶模糊函数估计平方累加后信号的最高项和次高项系数,重构信号对接收端信号降阶;采用奇异值分解(singular value decomposition,SVD)对基于三角窗减少干扰的核函数变换加以改进以提取降阶后信号的伪码序列。仿真实验表明了算法的有效性,当累加次数为20且信噪比在-4 d B以上时,伪码可以正确估计。
