基于遗传算法的MIMO-SAR面阵优化

Optimizing Planar Array in MIMO-SAR Radar Using Genetic Algorithm

传统的线阵MIMO-SAR必须经历一个合成孔径时间,才能获得高精度的雷达三维图像。这就势必降低了成像的实时性,而面阵MIMO-SAR很好地解决了这一问题。研究了MIMO-SAR雷达在发射接收天线孔径长度、最小阵元间距和阵元数目固定等约束条件下的平面阵列天线优化问题。MIMO-SAR采用稀布平面天线,基于天线相位中心近似原理建立了阵列优化模型,提出了一种交叉率和变异率可调的遗传算法进行阵元位置优化。该优化方法有效防止了遗传算法的早熟,解决了MIMO-SAR面阵天线低旁瓣电平和窄主瓣宽度双重设计问题。仿真结果表明了该优化模型的合理性及优化方法的有效性和优越性。

To achieve high precision radar three-dimensional images,the traditional linear antenna array MIMO-SAR must go through a synthetic aperture time,which will degrade the real-time imaging performance.But the planar antenna array MIMO-SAR can solve this problem very well.In this paper,the optimization of planar array antenna of MIMO-SAR radar is discussed under the conditions that the transmitting and receiving antenna arrays aperture lengths and the minimum array element spacing,and the number of array elements are constant.As MIMO-SAR adopts sparse planar antenna,based on the principle of antenna phase center approximation,an optimization model of array pattern considering sidelobes level and main lobe width is set up.In addition,agenetic algorithm based on crossover rate and mutation rate is proposed in order to solve array element position optimization model.The optimization method can suppress the premature of genetic algorithm effectively and solve MIMO-SAR array antenna double-design problems of low sidelobes level and narrow main lobe width.The simulation results show the effectiveness of the optimization method.