改进遗传算法优化MIMO稀布阵列

Modified genetic algorithm for optimizing MIMO sparse array

为了解决多输入多输出(MIMO)天线阵列由于阵元间隔过大造成的阵列方向图出现栅瓣,在雷达回波成像时出现影响目标识别的虚假目标的问题,提出了一种改进的遗传算法对阵列排布进行优化。在传统标准遗传算法上进行改进,用多个矩阵组合表示MIMO阵列,针对在矩形平面随机分布的稀疏阵列的方向图旁瓣问题进行优化设计,并采用基于Logistic混沌序列的方法产生种群扰动,避免优化过程进入局部最优状态。通过实例对比22发射天线22接收天线的均匀规则排布MIMO阵列和经改进遗传算法优化的稀布MIMO阵列,结果表明,改进遗传算法可以有效解决规则排布阵列方向图中出现的栅瓣,并且降低方向图旁瓣,提高雷达成像性能。该优化算法变量可控,具有很强的实用性,为MIMO雷达的阵列排布提供了解决方法。

The array pattern of Multiple Input Multiple Output(MIMO)antenna array has grating lobes due to the large array element spacing,and the false targets that affect the target recognition appear in the radar echo imaging.An improved genetic algorithm is proposed to optimize the array arrangement.The traditional standard genetic algorithm is improved to represent MIMO array with multiple matrix combinations,and the pattern sidelobes of sparse array with random distribution in rectangular plane are optimized.The method based on Logistic chaotic sequence is adopted to generate population disturbance and avoid the optimization process entering into the local optimal state.A uniform regular arrangement of MIMO array with 22 transmitting antennas and 22 receiving antennas and a modified MIMO array optimized by modified genetic algorithm are compared by examples.The results show that the modified genetic algorithm can effectively avoid the grating lobes in the regular array pattern,reduce the side lobes of the pattern,and improve the radar imaging performance.The optimization algorithm has strong practicability for its variable is controllable,which provides a solution for array arrangement of MIMO radar.