The Application of Convolutional Neural Network-Based Biological Radar Signal Classification Algorithm in Multi-target Vital Sign Detection

In recent years, with technological advancements, biological radar has been widely used in various environments for safety monitoring, health monitoring, environmental pollution control, air pollution monitoring, water pollution monitoring, air quality monitoring, food safety monitoring, water source pollution monitoring, and more. We can effectively separate and suppress motion noise through PCA technology while utilizing GoogLeNet technology to predict the number of moving targets in different environments accurately. Additionally, we introduce a novel Differential-Cross-Multiplication and State Space Method (DACM-SSM) to better explore and identify human identities. Experimental results demonstrate that this new algorithm significantly improves operational efficiency, resists data loss caused by random shifts in breathing and heartbeat, and mitigates interference from breathing harmonics. It reduces the complexity of current algorithms and saves more computational power, leading to more precise conclusions.