基于MUSIC算法的罗兰C接收机天地波自动识别方法研究

针对常规罗兰C接收机天地波识别方法不能有效利用信号能量的缺点,根据天波到来时间的估计与合成信号频率的分离相似的特点,提出了一种基于多信号分类算法估计天波延迟的方法.该方法在低信噪比条件下可分离出地波和天波,并能根据天波的延迟变化实时地选择接收机采样基准点的最佳位置.计算机仿真结果表明,该方法可以用于天地波的自动识别,能增加基准点处的信噪比,因而能显著提高罗兰C接收机的性能.

Loran-C receiver sky-wave detection based on MUSIC algorithms

In terms of sky-wave delay estimation and signal frequency separation,a new technique based on multiple signal classification algorithms which estimates the Loran-C receiver sky-wave delay is presented.The arrival time of ground-wave and sky-wave separately in poor SNR can be obtained and the datum-mark can automatically be adjusted to the best position according to the varying delays of sky-wave in real-time by the algorithms.The simulation indicates that the cycle ambiguity by re-(ference ) to the arrival time of ground-wave can be resolved,the SNR with tracking datum-mark can be increased,and the performance of Loran-C receiver can be significantly improved.Also,a frame of(realizing) this technique is presented.