Recognition method of dense false targets jamming based on time‐frequency atomic decomposition

• DOI: 10.1049/joe.2019.0147
• Publication Date: 2019-08-29T02:38:11Z
• Authors: Zhimei Hao; Wen Yu; Wei Chen
• Keywords: Gabor transform; SIGNAL (programming language); Feature (linguistics); Ambiguity function; Feature vector

Dense false target jamming can affect radar detection performance severely. A method of dense targets recognition based on time-frequency atomic decomposition theory and support vector machine (SVM) is proposed to solve the difficulty identification. According feature ambiguity function signal, a Gabor sub-dictionary which has adaptive variation with signal designed. The expanded into corresponding dictionary by sparse decomposition. After parameters are extracted as individual vectors, SVM utilised for classification recognition. experimental results show that effectively represent essential features jamming, respectively, this high rate.