Antenna position optimization method based on adaptive genetic algorithm with self‐supervised differential operator for distributed coherent aperture radar

The performance of the distributed coherent aperture radar (DCAR) is heavily influenced by antenna positions. Therefore, an position optimization method proposed based on adaptive genetic algorithm with a self-supervised differential operator. In method, positions are firstly coded as chromosomes population multiple constraints, and reciprocal peak side lobe level (PSLL) beam pattern calculated fitness function for optimization. Then, probabilities crossover mutation operator utilized in mutation. Finally, optimal DCAR can be obtained lowest PSLL compared existing methods. effectiveness verified linear planar DCARs, respectively.