基于压缩感知的塔康方位估计算法  

TACAN azimuth estimation algorithm based on compressed sensing

作　　者：姜力茹 许云达 高猛 JIANG Lim XU Yunda GAO Meng(Dalian Air force Communication NCO Academy,Dalian 116600, P. R. China)

机构地区：[1]空军大连通信士官学校,辽宁大连116600

出　　处：《重庆邮电大学学报（自然科学版）》2017年第3期365-370,共6页Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)

基　　金：国家自然科学基金(61273049)~~

摘　　要：塔康(tactical air navigation,TACAN)信号峰值检测后的离散数据呈随机采样特性,为避免Kalman算法产生滤波发散问题并有效减小对数据量的需求,提出一种基于压缩感知理论的方位估计方法。通过对塔康信号的角度空间进行稀疏分解和观测值压缩,优化重构原始包络信号进而获得方位估计值。仿真实验证明了该算法的性能,与最小二乘拟合算法相比,在保证估计精度的同时进一步降低了峰值数据量,大大减少了计算过程中的冗余,并且在信噪比较大的情况下,方位估计准确度较最小二乘拟合有一定提高。Discrete data of tractial air navigation （TACAN） signal peak detection is of random sampling. In this paper, In order to avoid filtering divergence of Kalman algorithm and effectively reduce the demand for data, a novel method of TACAN azimuth estimation is proposed based on compressed sensing theory. By performing sparse decomposition and ob-servation compression of TACAN angel space, the original envelope signal is reconfigured for optimization, and then the re-construction algorithm is used to recover the original signal and acquire the azimuth estimation. Experimental results show the performance of this proposed method. Compared with the other algorithm least square fitting, the method reduces peak data amount while ensuring estimation precision, which reduces the computation redundancy dramatically. Besides, in the case of large signal noise ratio （SNR） , this method shows better performance of accuracy than the least square method.

关 键 词：塔康(TACAN)信号 压缩感知 信号重构 方位解算 最小二乘拟合 

分 类 号：TN965[电子电信—信号与信息处理]