A novel alogrithm of signal pre-sorting based on random forest
LIU Xubo1, LIU Jingshu1, LIU Bin2, Qin Lingling2, CHEN Tao2
1. Unit 91977 of People's Liberation Army of China, Beijing 102200, China;
2. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
Abstract：In modern warfare, the radar electronic warfare environment is more and more complicated. With the variety of radar types and the complexity of radar inter-pulse modulation, the difficulty in identifying signal sorting is increasing. This paper proposes a random forest algorithm to sort the characteristics of pulse descriptors, which can daptively select features and achieve classification. Random forest can make the error balance of unbalanced data. Meanwhile through the multi-decision tree voting method, it can quickly complete the rapid training of large amounts of data. In the case of a pulse loss, the recognition accuracy can still be maintained. Experimental results show that the proposed method is effective in presorting radar pulse descriptors.
刘旭波, 刘敬蜀, 刘斌, 秦令令, 陈涛. 随机森林分类用于雷达信号预分选新算法研究[J]. 科技导报, 2019, 37(13): 93-97.
LIU Xubo, LIU Jingshu, LIU Bin, Qin Lingling, CHEN Tao. A novel alogrithm of signal pre-sorting based on random forest. Science & Technology Review, 2019, 37(13): 93-97.
2019, Vol. 37 
