最小概率DWO带宽选择及激光陀螺温度误差模型辨识

在原有研究的基础上,针对实验数据观测点疏密分布均匀或不均匀的工程实际情况,分别运用全局准则和局部准则,研究最小概率DWO非线性辨识方法中的带宽选择关键问题,提出了校正AIC准则和LCV准则两种不同的带宽选择方法,并将这些方法应用于四频差动激光陀螺的温度误差模型辨识中,比较和验证了这些方法的正确性和适应性。研究结果表明：①对于＂分布均匀＂的情况,宜采用校正AIC准则;②对于＂分布不均匀＂的情况,宜采用LCV准则;③形成了自动带宽选择算法。总之,这些方法为解决＂带宽选择＂问题提供了有效途径,从而进一步提高了最小概率DWO方法的工程应用价值。

Bandwidth selection of direct weight optimization with minimal probability and temperature error model identification of laser gyro

Based on the former researches, the bandwidth selection of minimal probability DWO(direct weight optimization) is investigated using global and local criterions respectively in view of the engineering practice situations (the observed points of test data are in uniform or non-uniform distribution). Two different bandwidth selection ways including corrected AIC (Akaike Information Criteria) and LCV (Local Cross Validation) criteria are presented and applied to identify the temperature error model of four-frequency differential laser gyro to compare and validate their correctness and adaptability. The research result shows: (1)In case of "uniform distribution", the corrected AIC should be adopted; (2)In case of "non-uniform distribution", the LCV criteria should be adopted; (3)Automatic bandwidth selection algorithms are developed. In a word, these methods are effective ways to overcome the problem of "bandwidth selection" and are able to advance the engineering significance of minimal probability DWO.