轨道不平顺信号的鲁棒参数估计与谱分析

轨道不平顺测量数据总会受到不同程度的污染。轨道谱的传统周期图估计和时间序列AR模型估计结果都对污染较敏感,算法缺乏鲁棒性。用鲁棒估计新理论对轨道不平顺随机信号进行鲁棒—稳固谱估计,并对估计的轨道谱曲线与传统轨道谱曲线进行对比,同时对观测数据加入脉动噪声后的轨道谱进行估计。结果表明,鲁棒估计谱对原始数据的干扰要求低,具有鲁棒稳健性。

Robust Parameter Estimation and Spectrum Analysis of Irregular Track Signal

The data got from irregular urack are always contaminated to different degree. Those traditional methods of track spectrum estimation such as Periodic-Graph Estimation and AR-Model Estimation of time domain sequence are sensitive to contamination, thus inevitably cause lacking of robustness. In this paper, a new technique of robust estimation called Robust and Steady Estimation is adopted to evaluate random signal of (irregular) track, and its curve is also compared with that of the traditional ones. Meanwhile, we also estimate the track spectrum when the observed data are added with pulse noises, which further demonstrates that robust (estimation) is less demanding to noise condition of original data.