TY - JOUR
T1 - Sidelobe Reduction for Similar Targets in Radar Pulse Compression Using Neural Network
AU - Hokmabadi, Alireza
AU - Zakeri, Arezoo
AU - Sharafat, Ahmadreza
PY - 2017
Y1 - 2017
N2 - We use a multilayer back propagation neural network whose training is based on Levenberg-Marquardt optimization method and apply polyphase codes to its input layer for radar pulse compression in environments with similar targets. The advantage of using polyphase codes (in contrast to binary codes) is lower sidelobe levels and much better Doppler tolerance. The use of Levenberg-Marquardt optimization method in our scheme significantly increases the speed of convergence. The results indicated that after 100 iterations, the main sidelobe for P3 code (N=30) is reduced to -238.66 dB and for P4 code (N=45), it is reduced to -240.51 dB. Besides, the proposed method is robust against noise and shows much higher Doppler tolerance.
AB - We use a multilayer back propagation neural network whose training is based on Levenberg-Marquardt optimization method and apply polyphase codes to its input layer for radar pulse compression in environments with similar targets. The advantage of using polyphase codes (in contrast to binary codes) is lower sidelobe levels and much better Doppler tolerance. The use of Levenberg-Marquardt optimization method in our scheme significantly increases the speed of convergence. The results indicated that after 100 iterations, the main sidelobe for P3 code (N=30) is reduced to -238.66 dB and for P4 code (N=45), it is reduced to -240.51 dB. Besides, the proposed method is robust against noise and shows much higher Doppler tolerance.
UR - https://jiaeee.com/article-1-389-en.html
M3 - Article
SN - 2676-6086
JO - Journal of Iranian Association of Electrical and Electronics Engineers
JF - Journal of Iranian Association of Electrical and Electronics Engineers
ER -