High Resolution Methods for Electronic Counter Measures Environments Establishing and Side Lobe Cancellation in Cognitive Radar
For high resolution methods for electronic counter measures environments establishing and side lobe cancellation in cognitive radar problems, dynamic modeling methods based on neural net were proposed to simulate the complicated electronic counter measures environments for cognitive radar, and the method based on selfadaptive neural net from cognitive computer of cognitive radar was also proposed to fix on the needed weights of amplitude or phase by means of the direction and intensity of jam resource. Dynamic modeling methods based on neural net was effective to solve some nonlinear mapping in traditional modeling question, to denote dynamic characteristic of electronic counter measures, to deal with multi-input and multioutput variants included by fix quantitative analysis, qualitative analysis. The method for side lobe cancellation in cognitive radar based on self-adaptive neural net solved the weight choosing problems of dynamic variety, adaptability, optimum, comparing with traditional weight choosing method such as MSE. Further, calculating time could satisfy the demand of cognitive radar operating real time. Simulation results showed that the resolved methods had superior performance on the accuracy and robust of electronic counter measures environments establishing and side lobe cancellation in cognitive radar.
Cognitive Radar Electronic Counter Measures Side Lobe Cancellation Neural Net Learning
Feng Zhou Tong Xu
College of Missile Air Force Engineering University Xian, China
国际会议
厦门
英文
805-808
2010-10-29（万方平台首次上网日期，不代表论文的发表时间）