Abstract: In order to avoid the interference between the same model radars, the radar signals are generally asked to be orthogonal, so to design orthogonal signals with low auto-correlation and cross-correlation is the key to anti-jamming. Concerning the frequency-coded radar signals, improved Particle Swarm Optimization (PSO) algorithm was used to optimize the signal-coding sequences selected from which to meet the objective function to find the orthogonal codes group. Crossover and mutation idea of Genetic Algorithm (GA) was introduced to overcome the slow convergence and local optimum of Simple PSO (SPSO) algorithm, and design results were analyzed at last. The results show that the method is effective and feasible, and the performance is superior to that of SPSO, Simulated Annealing (SA) and Hybrid Genetic Algorithm (HGA).

Key words: Particle Swarm Optimization (PSO), orthogonal coding, auto-correlation, cross-correlation, radar, anti-jamming

摘要： 为了避免同型号雷达发射信号之间产生的相互干扰，一般要求各雷达发射的信号是正交的，所以设计具有低自相关和互相关的正交编码信号是雷达抗干扰的关键。针对频率编码雷达信号，提出一种基于改进粒子群的正交编码信号优化算法，引入遗传算法中的交叉变异思想，从而克服基本粒子群算法(SPSO)收敛速度慢、易陷局部最优的缺点，最后对设计结果进行了分析。仿真结果表明，该方法是有效和可行的，在性能上要优于基本粒子群算法、模拟退火算法(SA)和混合遗传算法(HGA)。

关键词: 粒子群算法, 正交编码, 自相关, 互相关, 雷达, 抗干扰