Ground Target Recognition Method for Laser Proximity Fuze Echo Based on KNN Algorithm

Aiming at the urgent demand for accurate recognition of ground target by the new-generation of laser proximity fuze, an exploration study on ground target recognition using KNN algorithm based on the echo of the mission-target encounter of laser fuze is conducted. Firstly, the echo equation of mission-target encounter is established by the radar equation. Secondly, the echo data is processed by normalization, and the data is divided into the training dataset and the test dataset. Then, the data are subjected to feature extraction, such as the number of strong scattering points, equivalent target size. Finally, the obtained feature subset is used for target recognition training and testing based on KNN algorithm, linear support vector machine algorithm and Gaussian naive bayes algorithm. The experimental results indicate that the recognition method based on the KNN neighbor algorithm has high accuracy and can effectively achieve classification and recognition of different targets. It has a good application value in the recognition of lase ground fuze, and lays a solid foundation for the subsequent fine recognition and efficient destruction of laser fuze.