| 摘要: |
| 在选取信噪比作为信号质量指标的增强技术领域中，针对如何准确快速对复杂交叠的雷达信号进行信噪比估计的问题，改进了子空间分解算法，并且在求解自相关矩阵特征值时引入了结构简单、迭代速度快的粒子群优化(PSO)算法。通过设置不同的电磁环境场景，分别验证了算法的有效性。对比分析表明算法在低信噪比条件下具有明显的优势，为检验信号增强技术的效果提供了有力支撑。 |
| 关键词: 雷达信号质量 信噪比估计 子空间分解 粒子群优化 |
| DOI： |
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| 基金项目:国家自然科学基金资助项目（61571462） |
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| Radar signal quality estimation based on signal-to-noise ratio |
| GENG Changqing,YANG Chengzhi,TAO Jianwu,WANG Hongchao |
| (School of Aviation Operations and Services,Aviation University of Air Force,Changchun 130022,China) |
| Abstract: |
| In the enhanced technology field of signal-to-noise ratio(SNR) as a signal quality index,aiming at the problem of how to estimate the SNR of radar signals with complex overlapping quickly and accurately,the subspace decomposition algorithm is improved,and Particle Swarm Optimization(PSO) algorithm which is simple in structure and fast in iteration is introduced to solve the autocorrelation matrix eigenvalue.The effectiveness of the algorithm is verified by setting different electromagnetic environment scenarios.Comparative analysis shows the obvious advantage of the algorithm under the condition of low SNR,which provides a strong support for testing the effect of signal enhancement technology. |
| Key words: radar signal quality SNR estimation subspace decomposition particle swarm optimization（PSO） |
