吴儒杰, 金蛟, 李慧. 雷达测量误差的自回归分布滞后建模与仿真[J]. 北京师范大学学报(自然科学版), 2023, 59(2): 299-305. DOI: 10.12202/j.0476-0301.2022310
引用本文: 吴儒杰, 金蛟, 李慧. 雷达测量误差的自回归分布滞后建模与仿真[J]. 北京师范大学学报(自然科学版), 2023, 59(2): 299-305. DOI: 10.12202/j.0476-0301.2022310
WU Rujie, JIN Jiao, LI Hui. Modeling and simulation of radar measurement errors by the autoregressive distributed lag model[J]. Journal of Beijing Normal University(Natural Science), 2023, 59(2): 299-305. DOI: 10.12202/j.0476-0301.2022310
Citation: WU Rujie, JIN Jiao, LI Hui. Modeling and simulation of radar measurement errors by the autoregressive distributed lag model[J]. Journal of Beijing Normal University(Natural Science), 2023, 59(2): 299-305. DOI: 10.12202/j.0476-0301.2022310

雷达测量误差的自回归分布滞后建模与仿真

Modeling and simulation of radar measurement errors by the autoregressive distributed lag model

  • 摘要: 利用雷达的光测和误差数据,采用带变量滞后影响的自回归分布滞后模型(ADLM)与自回归条件异方差模型(ACHM),联合对雷测误差建模,刻画了雷测误差的统计特征,并对拟合优度及预测精度2方面,以及求和与分解这2种常用的非平稳时序模型进行了比较.结果显示,在该类雷测误差建模中,ADLM与ACHM的混合模型具有更高的拟合优度及预测精度.

     

    Abstract: Using the light measurement error data of radar, the autoregressive distributed lag model (ADLM) with variable lag influence and autoregressive conditional heteroskedasticity model (ACHM) are jointly built to describe the radar measurement errors. This model describes the statistical characteristics of the radar measurement errors , and compares the goodness of fit and prediction accuracy with the two commonly used nonstationary time series models: summation model and decomposition model. The results show that the mixed model of ADLM and ACHM has better goodness of fit and prediction accuracy in modeling this type of radar data.

     

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