For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosi...For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosine transform （DCT） to the outputs of the partial matched filter （PMF） for every antenna, the high order com- ponents in the transforming domain will be filtered, then the equalgain （EG） combination for the inverse discrete cosine transform （IDCT） reconstructed signal would be done subsequently. Thus, due to the different frequency distribution characteristics between the noise and signals, after EG combination, the energy of signals has almost no loss and the noise energy is greatly reduced. The theoretical analysis and simulation results show that the detection algorithm can effectively improve the signal-to-noise ratio of the captured signal and increase the probability of detection under the same false alarm probability. In addition, it should be pointed out that this method can also be applied to Rayleigh fading channels with moving antenna.展开更多
基金supported by the National Natural Science Foundation of China(61172138)the Natural Science Basic Research Plan in Shaanxi Province of China(2013JQ8040)+1 种基金the Fundamental Research Funds for the Central Universities(K5051302015K5051302040)
文摘For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosine transform （DCT） to the outputs of the partial matched filter （PMF） for every antenna, the high order com- ponents in the transforming domain will be filtered, then the equalgain （EG） combination for the inverse discrete cosine transform （IDCT） reconstructed signal would be done subsequently. Thus, due to the different frequency distribution characteristics between the noise and signals, after EG combination, the energy of signals has almost no loss and the noise energy is greatly reduced. The theoretical analysis and simulation results show that the detection algorithm can effectively improve the signal-to-noise ratio of the captured signal and increase the probability of detection under the same false alarm probability. In addition, it should be pointed out that this method can also be applied to Rayleigh fading channels with moving antenna.
文摘引入了压缩感知(Compressed sensing,CS)理论,给出了在获取局部二维离散余弦变换(Discrete cosine transform,DCT)系数的基础上高质量地编码与重构图像的新方法.研究了在无量化和有量化情况下,基于局部DCT系数的图像CS最小全变差重构算法.在对DCT系数进行量化的过程中得到含噪的局部DCT系数,在此基础上设计了能完成CS重构的图像编解码一般流程,并构建了实际应用系统.实验结果表明,对于稀疏性较强的图像,在图像编解码系统中结合CS理论与方法能得到高质量的重构图像,与传统的直接反离散余弦变换(Inverse DCT,IDCT)方法相比,峰值信噪比(Peak signal to noiseratio,PSNR)最大能提高5dB以上,对于一般图像,PSNR也有较大提高.
