Neural network methods for radar processing

Abstract

There are significant difficulties in radar automatic data processing arising from poor flexibility of known algorithms and low computational capacity of traditional computer devices. Neural networks can help the radar designer to overcome these difficulties as a result of computational power of neural parallel hardware and adaptive capabilities of neural algorithms. The idea of neural net application in the most difficult radar problems is proposed and analyzed. Some examples of neural methods for radar information processing are proposed and discussed: phase array antenna weights adaptation, genetic algorithms for optimization of multibased coded signals, data associations in multitarget environment, neural training for decision making systems. Results of the analysis for proposed methods prove that a considerable increase in efficiency can be achieved when neural networks are used for radar information processing problems.