Title :
A neural network sidelobe suppression filter for a pulse-compression radar with powers-of-two weights
Author :
Grishin, Yuri P. ; Zankiewicz, Andrzej
Author_Institution :
Dept. of Electr. Eng., Bialystok Tech. Univ., Grunwaldzka, Poland
Abstract :
A new compression filter for binary coded wideband digital signals with sidelobe reduction capabilities using a feedforward time-delay neural network is considered. This filter uses powers-of-two synaptic weights and the backpropagation learning algorithm. Using digital hardware implementation of such a filter for pulse compression is easier owing to elimination of multipliers. The simulation results showed that the time sidelobes of the output signal can be reduced up to about 60 dB. The quantization of the filter weights causes additional losses of about 6-14 dB depending on the input signal to noise ratio.
Keywords :
backpropagation; binary codes; data compression; digital filters; feedforward neural nets; interference suppression; pulse compression; radar interference; radar signal processing; 6 to 14 dB; 60 dB; backpropagation learning algorithm; binary coded wideband digital signals; compression filter; feedforward time-delay neural network; filter weights; input signal to noise ratio; losses; neural network sidelobe suppression filter; output signal; pulse-compression radar; quantization; sidelobe reduction; time sidelobes; Backpropagation algorithms; Digital filters; Feedforward neural networks; Hardware; Neural networks; Pulse compression methods; Quantization; Radar; Signal to noise ratio; Wideband;
Conference_Titel :
Electrotechnical Conference, 2000. MELECON 2000. 10th Mediterranean
Print_ISBN :
0-7803-6290-X
DOI :
10.1109/MELCON.2000.880033