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针对在固定阵元数目、最小阵元间距以及最大孔径条件下平面稀疏阵列阵形优化的问题,对阵元数目为256的平面稀疏阵列分别采用模拟退火算法和粒子群优化算法进行优化仿真,分析比较了模拟退火算法和粒子群算法在平面稀疏阵列阵形优化中的应用效果。仿真结果表明,经过模拟退火算法和粒子群优化算法优化后的平面稀疏阵列均能够抑制副瓣电平,并能够在一定的空域范围内实现波束扫描;相对于粒子群优化算法,模拟退化算法计算方法简单;在相同的迭代次数下,经模拟退火算法优化后的平面稀疏阵列比经粒子群算法优化后的平面稀疏阵列更能够有效地抑制副瓣。
Aiming at the optimization of array shape of planar sparse array with fixed array element number, minimum array element spacing and maximum aperture, simulated annealing algorithm and particle swarm optimization algorithm are used to optimize the planar sparse array with array element number of 256 respectively. The analysis and comparison The Application Effect of Simulated Annealing Algorithm and Particle Swarm Optimization in Optimization of Planar Sparse Arrays. The simulation results show that the plane sparse array optimized by simulated annealing algorithm and particle swarm optimization algorithm can suppress the sidelobe level and realize beam scanning within a certain spatial range. Compared with the particle swarm optimization algorithm, the simulated degeneracy algorithm The method is simple. With the same number of iterations, the planar sparse array optimized by simulated annealing algorithm is more effective than the planar sparse array optimized by particle swarm optimization.