基于优化序列提取的相控阵雷达识别方法

针对相控阵雷达工作模式识别的问题, 提出一种基于优化序列提取的雷达识别方法。首先，对相控阵雷达搜索和跟踪的工作模式进行分析, 建立工作模式序列模型。其次，通过剔除Needleman-Wunsch方法中的多余数据简化运算流程, 提出一种优化的雷达信号公共序列提取算法。然后，通过理论证明了所提算法的高效性, 并给出算法识别效果的评价准则。最后，结合雷达工作模型和所提算法, 对不同跟踪条件下雷达的识别效果进行仿真, 并对比了优化前后的运算时间。仿真结果表明, 所提算法在多种跟踪条件下, 均有较高的效率, 并且能保持91%以上的识别率。

Phased array radar recognition method based on optimized sequence extraction

Aiming at the problem of working pattern recognition of phased array radar,a radar recognition method based on optimized sequence extraction is proposed.Firstly,the working mode of searching and tracking for phased array radar is analyzed,and the working mode sequence model is established.Secondly,the operation process is simflified by eliminating the redundant data in Needleman-Wunsch method,an optimized radar signal common sequence extraction algorithm is proposed.Then,the efficiency of the proposed algorithm is proved by theory,and the evaluation criteria of the recognition effect for the algorithm is given.Finally,combined with the radar working model and the proposed algorithm,the radar recognition effect under different tracking conditions is simulated,and the operation times before and after optimization are compared.Simulation results show that the proposed algorithm has high efficiency under various tracking conditions,and can maintain a recognition rate of more than 91%.