Identification Method for RLG Random Errors Based on Allan Variance and Equivalent Theorem

An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances of all component noises inherent in noise sources in terms of their different equations; then the variances are used to estimate the parameters of all component noise models; finally, the original errors are represented by the sum of the non-stationary component noise model and the equivalent model mixed out of the stationary and critically stationary component noises. Results of two examples for identification confirm the superiority of this approach regardless of the errors being stationary or not. The comparison of results of real ring laser gyro (RLG) errors processed by various methods shows that the proposed approach is more suited to depict the original noises than common ones.     

基于盲解卷的雷达信号分选

盲信号处理是近年来信号处理领域的热点研究课题,可以根据输入源信号的基本统计特征,由观测数据进行信号分离,最终恢复出源信号。深入分析了非平稳信号的盲解卷算法,并提出了将其用于雷达信号分选的新思路。计算机仿真表明,这种算法应用于雷达信号分选时可以获得较好的分离效果,从而为实现现代电子对抗中复杂的雷达信号分选提供了新的思路。     

附面阻尼随频率变化的复合材料层合结构非平稳随机振动分析

 提出了对敷设粘弹性阻尼层的复合材料层合结构非平稳随机振动分析的高效精确算法。考虑了粘弹性阻尼材料对激振频率的依赖性及Adams提出的复合材料层合结构的阻尼模型。为解决依赖频率变化的非经典阻尼的复杂结构,结合实模态降阶直接解法对虚拟激励法做了相应的发展,并采用精细积分法高效精确地求解了随机振动方程。以国产有限元程序系统DDJ为平台开发了相应的程序,并对波音737客机的水平尾翼的复合材料安定面结构进行模拟研究,从复杂的计算及合理的结论可以看出,本文中所提出的方法对于这类十分复杂复合材料结构的非平稳随机振动分析十分有效。