Design of object detection system based on multi-source data

In contemporary battlefield environments, the deployment of unmanned equipment is becoming increasingly common and serves a critical role in intelligence gathering, surveillance, reconnaissance, and fire support. However, as a core enabling technology for unmanned platforms, battlefield target detection faces numerous challenges that restrict the operational effectiveness of these systems. Single-sensor detection approaches present technical limitations when operating under adverse weather conditions such as rain, snow and heavy fog, as well as in the presence of countermeasures including camouflage, decoy munitions and false targets. To address these limitations, a target detection system based on multi-source data has been developed and implemented. This system improves detection accuracy and robustness by integrating data from multiple sensors including visible light cameras, infrared imaging systems and LiDAR, thereby providing essential technical support for intelligent battlefield perception.