Low-angle estimation using frequency-agile refined maximum likelihood algorithm based on optimal fusion  

作　　者：CHEN Sheng ZHAO Yongbo PANG Xiaojiao HU Yili CAO Chenghu 

机构地区：[1]National Laboratory of Radar Signal Processing,Xidian University,Xi’an 710071,China

出　　处：《Journal of Systems Engineering and Electronics》2021年第3期538-544,共7页系统工程与电子技术（英文版）

基　　金：supported by the Fund for Foreign Scholars in University Research and Teaching Programs(the 111 Project)(B18039).

摘　　要：Low elevation estimation,which has attracted wide attention due to the presence of specular multipath,is essential for tracking radars.Frequency agility not only has the advantage of strong anti-interference ability,but also can enhance the performance of tracking radars.A frequency-agile refined maximum likelihood(RML)algorithm based on optimal fusion is proposed.The algorithm constructs an optimization problem,which minimizes the mean square error(MSE)of angle estimation.Thereby,the optimal weight at different frequency points is obtained for fusing the angle estimation.Through theoretical analysis and simulation,the frequency-agile RML algorithm based on optimal fusion can improve the accuracy of angle estimation effectively.

关 键 词：frequency-agile maximum likelihood multipath signal low-angle estimation 

分 类 号：TN957.51[电子电信—信号与信息处理]