# Optimization Design for Sparse Planar Array in Satellite Communications
## 4 Sparse Planar Array Optimization Design Method
### Intelligent Optimization Methods
#### 4.2.1 Sparse Area Array Optimization Based on Traditional Intelligent Methods
The authors of [49] reported a comparative evaluation of the proposed ACO method with the GA and IWO methods for an array of 10 elements and \(\varphi_{0}=0^{\circ}\). The results indicated that the _PSLL_ achieved using the ACO method was 3.4 dB lower than that obtained using the GA method. Additionally, the directivity achieved using the ACO method was 1.25 dB higher than that obtained using the GA method. Moreover, the _PSLL_ achieved using the ACO method was 5.4 dB lower than that obtained using the IWO method, and the directivity achieved using the ACO method was 1.88 dB higher than that obtained using the GA method. For large arrays, in [50], the ant migration path was used as the subarray division scheme, the peak sidelobe level was taken as the optimization goal, an adaptive beamforming method based on the ant colony algorithm was proposed, and the peak sidelobe level was effectively lowered. The advantages of the ant colony algorithm are its simple design, good robustness, easy parallel implementation, and the characteristics of implicit local search, but the disadvantage are its slow convergence and easy settling into a local optimum. In recent years, with the continuous development and improvement of intelligent algorithms, the main research trends have begun to gravitate toward the mixing and improvement of traditional intelligent algorithms and the proposal of emerging intelligent optimization methods, such as the use of biogeography-based optimization (BBO) to optimize the amplitude excitation of rectangular arrays, concentric circle arrays, and hexagonal arrays, which obtain a lower peak sidelobe level, but lead to a decrease in the directionality of the array shape [51]. In order to solve this problem, the authors of [52] used the teaching-learning-based optimization algorithm (TLBO) to reduce the peak sidelobe level of planar array, which does not need to tune parameters, shortens the algorithm processing time, and highlights the superior array pattern characteristics while effectively reducing the number of elements. The symbiotic organism search (SOS) algorithm [53] is used to design concentric circle arrays with the best peak sidelobe level, which significantly reduces the number of elements compared with the BBO algorithm and the TLBO algorithm, but can obtain lower sidelobes and has better robustness without tuning parameters. The study presented in [53] conducted a comparison of the thinning techniques of CCAA using SOS, BBO, and TLBO methods for an array of 440 elements. The results revealed that the BBO method employed 211 array elements to achieve a _PSLL_ of \(-\)26.58 dB. The TLBO method achieved a _PSLL_ of \(-\)28.82 dB by utilizing 215 array elements. However, the SOS method achieved a lower _PSLL_ of \(-\)31.18 dB with the use of 208 array elements. Aiming at the problem that the traditional intelligent method is slow to converge and easily falls into a local optimum, the authors of [54] used the whale optimization algorithm (WOA) to optimize the concentric circle array, which could obtain a low sidelobe level, while only a small number of iterations could obtain the global optimality, and the results could be prevented from falling into local optimum. The authors of [54] presented a comparative analysis of the PSO and WOA methods for thinning CCAA under identical array size conditions. The evaluation was conducted on a CCAA with 168 array elements, and the results indicated that the WOA method achieved a _PSLL_ of \(-\)27.98 dB by employing a reduced set of 87 array elements. In contrast, the PSO method required 97 array elements to achieve a slightly lower _PSLL_ of \(-\)27.81 dB. In order to optimize multiple targets at the same time, moth-flame optimization (MFO) was used to improve the far-field radiation characteristics of the antenna [55], resulting in a narrower zero beamwidth and a lower peak sidelobe level.