Array pattern control in the complex plane optimised by a genetic algorithm

A genetic algorithm (GA) is a robust stochastic search technique that mimics the process of natural selection by operating on a population of possible solutions. Each solution is represented by a “chromosome” containing several “genes”. The principle of “survival of the fittest” is used to “breed” improved solutions and, eventually, find a global optimum. GAs can require large amounts of computation, but often outperform other optimisation methods where analytic techniques cannot be used due, for example, to discontinuous or non-differentiable functions and where an optimisation has multiple objectives. GAs have been applied to optimisation in several electromagnetic problems. A GA, taking advantage of synthesis in the complex plane, is used to find the necessary complex weights for null steering adaptation of linear array antennas with performance constraints