Research on Signal Processing Algorithm of Infrared Chemical Remote Sensing Based on Digital Filter

  • Meitao Gong

Abstract

No matter which kind of signal transmission method, it has its own unique signal
characteristics. It is precisely because of these signal transmission characteristics that
people can process the signal by using advanced equipment, perhaps the signal source,
signal strength The change may also be a change in signal emission. For chemical
remote sensing signal processing technology, it is the development of sound generation
signal feature extraction technology. At the beginning, based on the traditional chemical
remote sensing signal processing thinking, the developers believed that the collected
chemical remote sensing The signal should only be linear or Gaussian, but with the
deepening of research and the continuous improvement of the equipment level, it is
found that the chemical remote sensing signal in chemical remote sensing is interfered
by many other external factors and the propagation process is not limited to only two
signal characteristics. . Currently, there are mainly the following two methods in the
feature extraction technology of sound emission signals. There are many signal
processing methods, such as mean, mean square, variance, autocorrelation function and
cross-correlation function. Other commonly used methods include support vector
machines and artificial neural networks. Through the above analysis, it can be found that
the kurtosis index is better for the early diagnosis of faults. Wavelet analysis is used
more for fault diagnosis. Cepstrum is mostly used for speech recognition. Now it is
getting more and more in the field of fault diagnosis. Many applications. It can be clearly
found that different methods have different advantages and the appropriate method
should be selected according to the specific conditions of the signal to achieve the best
results.

Published
2020-11-01
Section
Articles