Ultra-wideband multi-channel signal parallel processing analysis method and ultra-wideband multi-channel signal parallel processing analysis system

Abstract

The invention discloses an ultra-wideband multi-channel signal parallel processing and analyzing method, which comprises the following steps of: S1, extracting original data to form M paths of parallel sampling data; S2, selecting a proper FFT point number; S3, performing complex multiplication on the N-point FFT operation result and the twiddle factor according to the channel where the N-point FFT operation result is located; s4, carrying out complex multiplication on the FFT operation result of the N points and the twiddle factor according to the channel and the sample point serial number ofthe N points; s5, performing interleaving on the data of each channel, and performing FFT operation to obtain M paths of parallel signal frequency spectrums; and S6, splicing the M paths of parallelsignal frequency spectrums to obtain a final result. The method has the advantages that real-time multi-channel interleaving operation is carried out in a multi-channel parallel mode, large-bandwidthreal-time spectrum analysis is effectively achieved, and multi-channel parallel operation analysis of large-bandwidth signals far exceeding the limit of the operation speed of hardware can be achievedat the limited hardware operation speed.

Description

technical field [0001] The invention belongs to the field of signal detection and processing, and in particular relates to an ultra-wideband multi-channel signal parallel processing and analysis method. Background technique [0002] With the advancement of technology, the development of modern wireless communication has brought great challenges to the detection and analysis of signals. For example, the detection and analysis of broadband signals transmitted and received by broadband wireless communication equipment such as radio stations, satellite communications, and data link terminals. The more and more extensive wireless communication applications cause the signal to have time-varying characteristics and a large number of short-lived events, and the bandwidth of the signal is also becoming larger and larger. To meet the real-time requirements of signal processing, signal analysis needs to be performed in FPGA hardware. However, limited by the internal processing clock ...

AI Technical Summary

Problems solved by technology

However, limited by the internal processing clock frequency of the FPGA, the existing signal detection and analysis methods have been unable to do what they want. Because the analysis needs to scan and traverse the entire analysis bandwidth in a certain step, the scanning time can be as long as several Ten seconds, during the scanning process, important instantaneous signals outside the current scanning frequency band are often missed, and the full frequency band information cannot be observed

Images