学术
摘 要:
该文利用神经网络进行高频地波雷达目标到达角估计。论文分别采用RBFN和GRNN构造了基于函数逼近和模式编码的到达角估计网络，介绍了网络结构、数据仿真的过程和应用于高频地波雷达目标定向的实际效果。数据仿真和现场实验的分析结果表明基于模式编码的GRNN网络到达角估计方法鲁棒性较好，在低信噪比时能够给出正确估计。[著者文摘]
文章出处:
《电子与信息学报》-2008年30卷2期 -339-342页
栏目信息:
分 类 号:
文献标识码:
A
文章编号:
1009-5896（2008）02-0339-04
DOA Estimation Based on Neural Network for HFGWR
Yan Song-hua ,Wu Shi-cai, Wu Xiong-bin （School of Electronic Information, Wuhan University, Wuhan 430079, China）
Abstract:
Direction of Arrival （DOA） technology based on neural network is discussed. In the paper, the DOA method based on function approach and model classification with coding is presented and it employs two kinds of neural networks： Radial Basis Function Network（RBFN） and General Regression Neural Net （GRNN）. The paper introduces the network structure, simulation and the application to High Frequency Ground Wave Radar（HFGWR）. The simulation and real data processing verifies that the model classification method based on GRNN offers better performance than others, its performance is good even the signal-to-noise of the signal is low until 4 dB.[著者文摘]
Key words:
Neural network; DOA; Model classification; HFGWR（High Frequency Ground Wave Radar）
基金资助:
国家自然科学基金（60571065）和国家863计划（20001AA631050）持续资助课题
更多>>免费文章
cqvip.com