The author of this article, maxfiner, graduated from Xi'an University of Electronic Science and Technology with a master's degree in signal and information processing. Maxfiner has worked in the wireless communication department of Huawei Communication Technology Co., Ltd., and has many years of experience in engineering project development. It also has algorithm theory research, simulation verification, and corresponding hardware design implementation capabilities. It has practical experience in all aspects of communication physical layer development and design. .
When it comes to signal processing, I have to mention the related concepts. The correlation function is a very important concept in the theoretical analysis of signal processing (such as Wiener-Sinqin's theorem: the correlation function of the random signal and the power spectrum is a pair of Fourier transforms). The correlation matrix of signals is the object of research, analysis and processing of many signal processing algorithms. Correlation is not only a very theoretical concept, but also a widely used processing method and effective processing method in practice. It has a wide range of applications in synchronous detection, navigation, positioning, electronic reconnaissance, delay estimation, and spectral estimation of communication receivers.
In the following series of articles, the list of winds will be enumerated as follows:
The first example: detecting signals that are submerged in noise.
The second example is the synchronous detection and reception of the communication receiver, and the synchronization processing of the symbols is completed by the detection processing of whether or not the relevant accumulation completion signal arrives.
The third example: Spread spectrum technology is to construct the pseudo-random code with good autocorrelation property, which greatly enhances the anti-interference ability of the communication system, and performs synchronous detection based on the relevant accumulation processing. Its most typical applications are mainstream 3G communication systems such as CDMA, TDS-CDMA, and CDMA2000.
The fourth example: whether it is the GPS in the United States or the Beidou system in China, the acquisition of navigation signals can detect and capture signals at very low signal-to-noise ratios through long-term correlation accumulation of signals.
The fifth example: the signal delay estimation of the analog transmission channel, the peak of the correlation function can be used to estimate the delay of the channel.
The sixth case: related processing plays a key role in the field of radio monitoring, direction finding and positioning, and plays an important role.
The seventh example: In the classical and well-known LMS adaptive signal processing, by analyzing the eigenvalues ​​of the signal autocorrelation matrix, it can be determined how much the LMS iteration step should be taken to prevent the LMS iterative process from diverging.
The eighth example: the channel correction of the zero-IF receiver channel, the correction parameters of the channel can be solved based on the correlation matrix of the input distortion signal, and the distortion signal is corrected, thereby eliminating the spectrum imbalance caused by the gain imbalance and phase imbalance of the receiving channel. .
Ninth example: The classical spectral estimation method, the BT method, is based on the correlation function of the signal.
The tenth case: modern spectral estimation methods, such as the AR model based parameter spectrum estimation method (maximum spectrum estimation method), MUSIC method, Pisarenko harmonic decomposition method, ESPRIT rotation invariant method, etc., all are closely related to the correlation function. The signal-based correlation matrix is ​​processed accordingly.
It can be seen that the relevant aspects of engineering practice have a wide range of applications. The concept of correlation function and the nature of the correlation matrix deserve our repeated recollection and understanding. They are the basis for our understanding of signal processing theory and a tool for solving practical problems. In the follow-up, we will discuss in detail the specific application of related concepts in these areas, so as to better understand the wonderful features and great power of related functions!
The next issue is to speak - proficient in signal processing design, small TIps (8): to detect the periodic signal submerged in the noise, so stay tuned!
Disclaimer: Electronic enthusiast network copyright, declined to reprint!
Proficient in Signal Processing Design Small TIps(1): Signals and Information
Proficient in Signal Processing Design Small TIps(2): The Role of Mathematics
Proficient in signal processing design, small TIps (3): the three cornerstones that must be mastered
Proficient in Signal Processing Design Small Tips(4): Several Signals Used Most Frequently
Proficient in Signal Processing Design Small Tips(5): Three widely used mathematical concepts
Proficient in signal processing design Tips (6): How is convolution obtained?
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