Design and Implementation of Distributed Radar Multi-Source Data Fusion Software Based on Qt

Distributed radar multi-source data fusion improves target tracking accuracy and system situation awareness by fusing detection data from multiple radar sites. Based on the actual needs of radar data fusion, this paper uses the Qt framework to design and develop distributed radar multi-source data fusion system software under the Windows operating system, and implements key algorithms such as track filtering, track normalization, track bifurcation, and redundant track elimination. The software system adopts a multi-threaded architecture, combines QPainter to achieve two-dimensional radar scanning visualization, and uses the Qwt3D open source library to build a three-dimensional trajectory visualization module to achieve efficient rendering and three-dimensional dynamic display of target motion trajectories. Test results show that the system can effectively fuse multi-source target track data and run stably in complex environments. At the same time, Qt's cross-platform characteristics enhance the compatibility and scalability of the software, laying the foundation for subsequent fusion algorithm migration and multi-scenario applications.