Research On Microwave Photonics Signal Monitoring System Based On DSP

With the development of modern information technology,wireless communication technology is rapidly changing society and everyday life.However,the accompanying problem is that the communication environment of radio frequency signals is becoming increasingly complex,the frequency spectrum resources of the lowfrequency band are almost depleted,and the highest frequency that traditional electrical signal monitoring systems can measure is difficult to surpass the "electronic bottleneck." On this basis,microwave photonics frequency measurement technology has brought new development prospects for measuring higher frequency bands of radio frequency signals.Optical processing methods can achieve larger measurement bandwidth,lower transmission loss,smaller size,and lower power consumption.Due to the fact that most of the observation devices used in microwave photonics frequency measurement systems are discrete devices such as oscilloscopes or spectrum analyzers,the system structure is not only bulky but also costly,making it difficult to develop a productized microwave photonics radio frequency signal receiver,which is still in the laboratory stage.With the development of DSP technology,it has good applicability for processing large amounts of data and has significant advantages in achieving high-speed,real-time digital signal processing.It is portable,lightweight,and cost-effective.This article selects DSP to implement the digital processing analysis of the backend of the microwave photonics frequency measurement system and replaces testing equipment such as oscilloscopes.This thesis proposes a backend signal processing scheme based on DSP processor for microwave photonics frequency measurement system.In terms of hardware design,the front-end microwave photonics link is constructed to realize signal acquisition and down-conversion processing,and the DSP chip selection and relevant peripheral circuit design are completed for the performance requirements of the backend.In terms of software,a DSP program based on the C language is designed in the CCS integrated development environment,mainly designing the acquisition module,data transmission program between DSPs,and frequency domain analysis algorithm.A processing scheme based on the FFT algorithm for frequency spectrum analysis of down-converted signals is proposed,and an external device driver program is designed to output the processing results through an LCD screen.The proposed microwave photonics signal monitoring system is simulated and analyzed in Optisystem,and the overall system is built for actual testing to verify the feasibility of the system.In the test of simulated RF signals,the measurement error of the system for intermediate frequency signals is 0.24 MHz within the measurement range,the highest system sensitivity is-30 d Bm,and the dynamic range is 55 d B.In the actual testing of mobile phone RF signals,the measurement error is only0.11 MHz.The system has high real-time performance and stable performance.This module provides an embedded device for the backend processing of the microwave photonics frequency measurement system and provides a certain foundation for future research and application.To address the error problem in the measured mobile phone signal,optimization design is carried out.Considering the fixed hardware indicators,sampling rate and other performance factors,the measurement performance of the system is further enhanced by improving the FFT algorithm,making the measured value closer to the actual value.By simulating the zoom FFT algorithm in MATLAB,the measured mobile RF signal is input into zoom FFT,and the frequency spectrum area near the peak is analyzed locally to more accurately extract the frequency information of the peak,thereby reducing the measurement error of the system.In the simulation experiment,the actual 46.49 MHz signal was analyzed by the original FFT algorithm,and the measurement result was 46.386 MHz.After being analyzed by the zoom FFT algorithm,the measurement result was 46.500 MHz,and it was verified that the improved algorithm reduced the measurement error within a certain frequency spectrum range.