Broadband low-insertion-loss surface acoustic wave filter set for realizing wavelet transformation

Abstract

The present invention provides a broadband low-insertion-loss surface acoustic wave filter set for realizing wavelet transformation. The broadband low-insertion-loss surface acoustic wave filter set is characterized in that: the broadband low-insertion-loss surface acoustic wave filter set is composed of N channels of broadband low-insertion-loss surface acoustic wave filters, wherein N is larger than or equal with 1; each broadband low-insertion-loss surface acoustic wave filter is a linear phase wave filter and has equal delay time; the Q-value of each broadband low-insertion-loss surface acoustic wave filter is same; the central frequencies of the broadband low-insertion-loss surface acoustic wave filter increase progressively through a fixed multiple; and furthermore the broadband low-insertion-loss surface acoustic wave filters are crossed at the 3dB bandwidth. The broadband low-insertion-loss surface acoustic wave filter set settles problems of high difficulty of realizing real-time processing in wavelet transformation or requirement for fixed delay time in a signal processing circuit. Each channel of wave filter has linear phase and same group delay. The broadband low-insertion-loss surface acoustic wave filter set has the following characteristics: broad band, low insertion loss, and high suitability for intermediate frequency analog signal processing in a communication system.

Description

technical field [0001] The invention relates to a wide-band low-insertion-loss surface acoustic wave filter group for realizing wavelet transformation, belonging to the field of communication signal processing. Background technique [0002] Wavelet transform is a new branch of mathematics under development. At the same time, as a signal processing method, it has become an important mathematical tool for scientific and technological workers in the field of engineering applications, and has achieved remarkable results in many engineering applications. Compared with the traditional Fourier transform signal processing method, because it overcomes the disadvantage of poor time-frequency resolution of window Fourier transform and has multi-resolution analysis function, it is widely used in communication signal processing and other fields. [0003] The wavelet transform algorithm is complex. In engineering applications, it is generally required to process the signal in real time or...

AI Technical Summary

Problems solved by technology

[0003] The wavelet transform algorithm is complex. In engineering applications, it is generally required to process the signal in real time or require the signal processing circuit to have a fixed delay time, so it is difficult.

In the existing wavelet transform technology using surface acoustic wave devices, in order to realize wavelet transform, the delay time between surface acoustic wave devices of different scales is different from each other, resulting in asynchronous signal processing. The surface acoustic wave device of this scale can only be eliminated by delay circuit compensation, making the overall volume larger and difficult to be practical

Moreover, the prior art adopts a bidirectional transducer-bidirectional transducer structure (BDT-BDT structure), such as figure 1 As shown, the insertion loss of the surface acoustic wave device is relatively large, which seriously restricts its application in the signal processing of the communication system

In addition, the early devices that implement wavelet transform have a narrow bandwidth (1.5% of the relative bandwidth), and cannot meet the application requirements of large bandwidth.

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