Infrared and Laser Engineering, Volume. 47, Issue 8, 826005(2018)
Radar target recognition based on central moment feature and GA-BP neural network
When using the method of kernel principal component analysis(KPCA) to extract feature of target in radar target recognition, the HRRP characteristic is ignored. A translation invariant features-central moments was extracted as feature vector, KPCA was used to reduce the dimensionality; The BP neural network was easy to fall into local minimum, the genetic algorithm(GA) was used to optimize the BP network node weights and threshold. The experimental results based on the measured radar data show that the translation invariant KPCA feature extraction method achieve the combination of translation invariant and descending dimension, and the BP neural network optimized by GA improves the stability of classifier and improves the defect of falling into local minimum easily.
Get Citation
Copy Citation Text
Zhao Dongbo, Li Hui. Radar target recognition based on central moment feature and GA-BP neural network[J]. Infrared and Laser Engineering, 2018, 47(8): 826005
Category: 信息获取与辨识
Received: Mar. 9, 2018
Accepted: Apr. 12, 2018
Published Online: Aug. 29, 2018
The Author Email: Dongbo Zhao (alien_dffy@163.com)