Optimal Design of Group Orthogonal MIMO Radar Waveforms Bases on Quantum Genetic Algorithm

Digital radio frequency memory (DRFM) devices can quickly intercept radar waveforms and has become the main technique to achieve advanced radar jamming. Multiple-input multiple-output (MIMO) radars can counter advanced DRFM jamming based on waveform agility technology by emitting waveform sets which are orthogonal between groups. To design multiple groups of orthogonal waveform sets simultaneously, an optimization design model for group agile orthogonal waveform sets is developed in this paper. The correlation function peak of intergroup waveforms is multiplied by a deviation weight, serving as the objective function. In order to solve the proposed optimization model, we propose an optimization design algorithm for group agile orthogonal waveform sets. The quantum genetic algorithm (QGA), employing a partial search strategy and having no special requirements on the properties of the objective function, is capable of solving such complex non-convex optimization problems. Numerical simulation results demonstrate that the proposed algorithm yields waveform sets with good intra- and intergroup orthogonality performance, adjustable via changing weight coefficients.