节点文献
用TH神经网络方法外推数据的超分辨雷达成象
SUPERRESOLUTION RADAR IMAGING WITH EXTRAPOLATING DATA USING NEURAL NETWORK
【摘要】 研究用Tank-Hopfield神经网络(THNN)求解AR模型参数作数据外推的超分辨雷达成象,并用微波暗室实测数据对THNN方法和Burg方法作了验证,结果表明,两种方法均能在较低的信噪比条件下实现超分辨成象,且随着VLSI技术的发展,神经网络方法将是一种很有希望的超分辨成象方法。
【Abstract】 ata extraploation super-resolution radar imaging with AR parameters estimated by Tank-Hopfield neural network(THNN)is investigated,and the real data in the microwave anechoic chamber are proeessed by the TH neural network method and Burg method.Imaging results indicate that both methods can complete superresolution imaging under the lower SIN,and with the developing of the VLSI technology,the neural network method will be a very promising super resolution imaging method.
【关键词】 雷达成象;
高分辨率;
线性预测;
人工智能;
【Key words】 radar imagery; high resolution; linear prediction; artificial intelligence;
【Key words】 radar imagery; high resolution; linear prediction; artificial intelligence;
【基金】 航空科学基金
- 【文献出处】 航空学报 ,ACTA AERONAUTICA ET ASTRONAUTICA SINICA , 编辑部邮箱 ,1994年08期
- 【分类号】V243.2
- 【下载频次】70