风洞自由飞试验中气动参数辨识准度评价方法研究

当高超声速风洞自由飞试验的测量数据被有色噪声污染时，传统的Cramér-Rao界作为参数估计准度的度量往往过于乐观。文本采用一种修正协方差方法来处理传统的最大似然估计的残差，以便计算出有色残差情况下精确的Cramér-Rao下界，对辨识参数结果进行不确定度评价。以10°半锥角尖锥模型为例，通过大量的Monte Carlo仿真试验和风洞试验验证了修正协方差方法的有效性。结果表明，在风洞试验测量存在有色噪声情况下，修正协方差方法给出的标准差均值约为传统的Cramér-Rao界方法给出的标准差的3~5倍，与参数估计的统计标准差一致，客观反映了参数辨识结果的精准度。

Research on accuracy assessment method of aerodynamic parameters identified from wind tunnel free-flight test data

The conventional Cramér-Rao lower bounds method is too optimistic to be a good quantitative assessment of the accuracy of aerodynamic parameters identified from the wind tunnel free-flight test data, considering the colored noise in the measurement data. This paper introduces a technique, that modified covariance matrix method, to process the residuals from a conventional maximum likelihood estimation to compute the accurate Cramér-Rao lower bounds for colored residuals. The modified accuracy assessment method is validated by Monte Carlo simulation and wind tunnel tests of pointed cone models with the semi-cone angle being 10°. The identified results indicate that the Cramér-Rao lower bounds calculated by the modified covariance matrix method are 3~5 times the quantity of the conventional. The modified results can be used as an accurate and impersonal assessment of the aerodynamic parameters estimated, which are consistent with the sample standard errors for the estimated parameters for colored residuals.