Application of Improved Northern Goshawk Optimization Algorithm in Radar Networking Optimization

Aiming at the characteristics of many problems and difficulties in the optimization of radar system networking, a mathematical model of radar optimization networking is established, and an improved northern goshawk optimization algorithm is proposed. The algorithm initializes the population through the cubic chaotic map, adds nonlinear weight factors, and uses the Cauchy-Gaussian mixture mutation operator to perturb, and achieves a better optimization effect than the basic northern goshawk algorithm. Then, the improved northern goshawk optimization algorithm is used to solve the established radar optimization networking model, and two algorithms are selected for comparative analysis. Simulation experiments show that the radar networking scheme optimized by the improved northern goshawk optimization algorithm is effective, feasible and better.