With the advent of new digital receiver exciters it is now feasible to generate innovative waveforms that can adapt rapidly to meet changing environments and scenarios. In order to meet the numerous and diverse objectives of this request for proposal we propose an approach that combines recent advances in the area of radar waveform design based on chaotic systems, multisensor data fusion based on the multistatic ambiguity function, and waveform optimization based on the use of genetic algorithms. Newly developed chaotic waveforms possess many desirable characteristics such as good range resolution, low range side-lobes and good average to peak transmit power ratio. In addition, their wideband spectrum makes them robust to jamming and other countermeasures. We propose to apply these near-orthogonal waveforms in radar configurations with multiple transmitters and multiple receivers. We intend to utilize the multistatic ambiguity function to assist in waveform design in order to meet desired radar performance criteria. Furthermore, to find favorable solutions to this complex nonlinear problem we will use genetic algorithms which provide a flexible and effective tool for waveform optimization.
Keywords: Multistatic Radar, Chaotic Waveforms, Genetic Algorithms, Ambiguity Function, Data Fusion
