A Comprehensive Collection of Array Antenna Pattern Synthesis Methods

Array antenna pattern synthesis is a key technology that achieves desired radiation characteristics by optimizing the excitation and arrangement of antenna elements. Main methods include:

Particle Swarm Optimization (PSO) This bio-inspired algorithm simulates bird flock foraging behavior, iteratively adjusting element parameters (such as amplitude and phase) to gradually approach the optimal radiation pattern. Its strength lies in strong global search capability, making it suitable for nonlinear and multi-peak optimization problems. Implementation typically involves initializing particle positions/velocities, defining fitness functions based on pattern requirements, and updating parameters through velocity and position equations.

Convex Optimization Method This approach transforms pattern design problems into convex optimization models solved through mathematical programming. It features high stability and guarantees convergence to global optima, particularly suitable for scenarios with clear constraints like sidelobe suppression and beamforming. Code implementation often employs optimization toolboxes with proper constraint formulation and objective functions.

Taylor Synthesis Method An analytical method based on Taylor series expansion that achieves low sidelobe beams by controlling current distribution. It offers high computational efficiency but limited flexibility, typically applied to uniform linear arrays. Implementation involves calculating Taylor coefficients and applying appropriate weighting functions to array elements.

These methods have distinct characteristics: PSO suits complex requirements but requires substantial computation; convex optimization provides high precision but depends on model simplification; Taylor method is fast but has limited adaptability. Practical applications often require selection or hybrid usage based on specific indicators like sidelobe level and computational resources.