中文摘要：

针对功率倒置阵列采用最小均方（LMS）算法不能兼顾收敛速度和稳态误差的问题，以及采用递归最小二乘（RLS）算法运算量增大，实现复杂等缺点，提出采用时变适用度函数的粒子群优化（PSO）算法．通过引入可变的惯性因子、可变的最大速度、选择机制等操作，自适应调整阵列权系数来寻找最优权值．将此算法应用于功率倒置阵列中能有效地生成零陷抑制干扰．

英文摘要：

The convergent speed and steady-state misadjustment error can not be improved simultaneously in the power inversion array when using the least mean square（LMS） algorithm. However, the recursive least squares （RLS） algorithm used in the power inversion array also bears a burden of large computation and is realized with difficulty. To solve this problem, the particle swarm optimization （PSO） algorithm adopting the time-varying fitness function is proposed. By means of introducing such techniques as the variable inertia factor, variable maximum speed and weight coefficients adaptively to find the best solution can place nulls to suppress jamming effectively.