本文研究的是OFDM系统中的信噪比估计算法．并利用DSP芯片．通过AD6640和AD6620组成中频接收平台，将其应用到实际的OFDM传输系统中。
This paper is the study of OFDM SNR estimation algorithm system, using DSP chips and IF receiver platform composed by AD6640 and AD6620 to apply it in actual OFDM transmission system.
通过实验表明，该方法较其它方法简单有效，即使在较低信噪比的情况下，也能对极点作出较好的估计。
The experimental results demonstrate that the method can give a better estimation of poles of damped exponential signals even in a lower signal-to-noise ratio (SNR) situation.
对于MPSK信号而言，信噪比的估计可以直接转化成对信号模的估计问题。
For MPSK signals, the signal-to-noise ratio (SNR) estimation can be directly transformed into the signal module estimation.
作为MAP译码算法的必要参数，信噪比通常通过信道估计单元得到。
As a necessary input parameter for MAP decoding algorithm, SNR was normally obtained from the channel estimation unit.
应用子空间扰动分析研究了宽带CSS法的统计性能，得出了宽带CSS法方位估计误差随信噪比变化的关系。
By using subspace disturbing analysis to investigate the statistical performance of the CSS, the relationship between the DOA estimation error and the signal to noise ratio (SNR) was presented.
与已有线性最小均方差(LMMSE)信道估计方法相比，该算法简单并且不需要预先知道信道相关矩阵以及信噪比等信道信息。
Comparing with the Linear Minimum Mean Square Error (LMMSE) channel estimation method, the method is simple and need not know the channel correlation and signal-to-noise (SNR).
目前的处理方法普遍需要估计噪声或者信噪比，从而其性能依赖于噪声估计的好坏。
Most resent approaches to the problem employ noise estimate or Signal-Noise Ratio (SNR) estimate, and hence their performances depend on the estimation of noise.
该文从理论和仿真两个角度研究了信噪比对多普勒中心频率估计的影响，给出了多普勒中心频率和信噪比的理论及仿真关系曲线。
The effect of Signal-Noise-Ration (SNR) to the estimation of Doppler central frequency has been studied using theoretical method and simulation technique, and results are given in curves.
此法大大地提高了有效的信噪比(SNR)和自相关矩阵的估计精度。
The effective signal-to-noise ratio (SNR) and the accuracy of autocorrelation estimation are significantly improved through use of this method.
主要介绍了一种典型的信噪比估计算法，并对信噪比的自相关矩阵奇异值分解估计法进行了研究。
This paper introduces a typical SNR estimation algorithm by the use of autocorrelation matrix singular value decomposition method.
本文最后讨论了自适应编码中的关键技术——信噪比估计算法。
At the end of this paper SNR estimation algorithm is discussed which plays an important role in adaptive coding technology.
针对短码实值混沌直扩系统，提出了一种基于主元分析的算法，实现了在低信噪比下对直扩序列的盲估计。
A new method of blind estimation for short-code chaotic spread spectrum sequence is proposed, which is based on principal component analysis (PCA) and has good performance at low SNR condition.
最后，论文提出了一些新的自适应技术，如波特率估计、信噪比估计等，并给出了应用这些技术的自适应调制解调器的改进方案。
Finally, the thesis proposes several newly adaptive technologies, like the estimation of baud rate and SNR. And corresponding improvements are also discussed.
最后作者提出一种改进型LS信道估计算法，该算法考虑了LS算法中噪声的影响，从而提高了低信噪比下信道估计的精度。
Finally, an improved channel estimation algorithm based on LS algorithm is presented. Considering the infection of the noise, the new algorithm has better performance under low SNR.
并采用新的相位估计方式估计含相位噪声的载波相位，提升了该条件下的环路信噪比。
With improved phase estimation method, a carrier signal phase with phase noise can be estimated, while loop SNR also increases.
噪声功率谱估计和先验信噪比估计的准确性有助于提高增强后的语音质量。
Correct noise power spectrum estimation and apriori signal-to-noise ratio (SNR) estimation are all essential to good quality of the enhanced speech.
噪声功率谱估计和先验信噪比估计的准确性有助于提高增强后的语音质量。
Correct noise power spectrum estimation and apriori signal-to-noise ratio (SNR) estimation are all essential to good quality of the enhanced speech.
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