Subband Adaptive Reconstruction Method Based on Digital Bandwidth Interleaving Acquisition System

In high-speed acquisition systems, digital bandwidth interleaving(DBI) acquisition technology can effectively improve the system's bandwidth. In practical sampling scenarios, the characteristics of the signal are often the sparse distribution of a small number of narrow channels in the broadband range. For full bandwidth sampling, the subbands of the blank frequency band only contain noise. This merging of frequency bands containing only noise can lead to a decrease in system performance. Therefore, this paper proposes a subband adaptive reconstruction method based on the DBI acquisition system to improve the performance of the acquisition system. In this method, the sparse Fourier transform(SFT) algorithm is used to perform real-time spectral analysis, determine the frequency range of the input signal, and select the spectral subbands with input signals for merging. This method has been implemented in a high-speed acquisition system with a sampling rate of 80GSPS and a bandwidth of 20GHz. After testing, using this method in the system has increased the effective number of bits(ENOB) by 1.86 bits and the signal-to-noise ratio(SNR) by 11.2dB at a frequency of 10.9GHz. The experimental results show that this method can effectively improve the ENOB and SNR of the DBI acquisition system, providing an effective solution for optimizing the performance of high bandwidth and high sampling rate acquisition systems.