Component-based Spectrum Monitoring Software Design And Implementation

With the rapid progress and development of computer technology and radio technology,radio monitoring increasingly tends to be automated,intelligent,and miniaturized,and requires monitoring products to provide a good user interface in order to better observe and manage the radio spectrum.At the same time,spectrum monitoring should also have a signal recognition function.After detecting a signal in the target frequency band,the signal abnormality/normal type can be determined based on the parameters such as the center frequency and bandwidth of the signal.In order to realize the automation,standardization and generalization of spectrum monitoring,this thesis designs and develops a spectrum monitoring software with accurate signal identification,intelligent monitoring,convenient setup,and user-friendly interface.This thesis works according to the development needs of spectrum monitoring software,analyzes and compares existing spectrum application software,and develops spectrum monitoring software based on software programming and graphical interfaces and other related technologies.In order to realize the cross-platform and friendly and smooth user interface for spectrum monitoring software,Qt Creator is used as the development platform to introduce the QtP third-party open source library QCustomPlot to develop spectrum monitoring software.In order to make the spectrum monitoring software have good maintainability and expansibility,this thesis follows the modularized,componentized development idea,and divides the components within the module on the basis of module division.The main work of this thesis on component-based spectrum monitoring software design and development is divided into two parts:At the software level,the software architecture of the original spectrum analysis software in the teaching and research section is used to optimize its inadequacies and the overall design of the spectrum monitoring software is designed,including the software architecture,module partitioning,hierarchical relationships,and multi-threading mechanisms.Modularization and componentized development concepts are used to develop spectrum monitoring software.Spectrum monitoring software is mainly divided into data processing module,driver module,network communication module and user interface module.The user interface is in turn divided into multiple display components,such as spectrogram display components,waterfall map components,and the like.In terms of algorithm,this thesis proposes a signal recognition algorithm for spectrum data.This algorithm combines and improves the K-Means clustering algorithm in pattern recognition to extract the background noise of different frequency bands during spectrum monitoring.Then use the peak value in the spectrum data and the extracted noise to extract the signal feature parameters and identify the signal.After software testing,it finally proved that the spectrum monitoring software generally meets the expected requirements and meets the requirements.