A Radar classification system based on Gaussian NB
Zili Ding, Jianxin Guo, Zhaosheng Shao, Hangjie Zhu · 2022
Radar recognition has gradually been widely used in daily life, especially in target recognition target classification has a good development prospect. With the rapid development of deep learning, a new material object classification system appears, and a radar classification system based on GaussianNB is proposed. We use radar to identify air,books, hands, knives and plastic boxes. By labeling the returned radar signals and conducting supervised training on them, classification models can be obtained and tested using these radar signals. The accuracy of GaussianNB algorithm is 96.36%. However, the accuracy of KNN algorithm is 92.14%, and the accuracy of gradient elevation decision tree is only 88.92%. This shows that GaussianNB based radar subsystem is more effective and accurate.