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Guidance Instrumentation Systematic Error Separation Method Based on Particle Swarm Optimization

机译:基于粒子群优化的指导仪器系统误差分离方法

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A new separation method of guidance instrumentation systematic error of vehicle based on particle swarm optimization (PSO) was proposed. The telemetry environment function matrix is seriously ill-conditioned, which results in the performance degradation of guidance instrumentation systematic error separation. Hereby the problem of guidance instrumentation systematic separation is transformed into an optimization problem and PSO is used to estimate the systematic error coefficients. Furthermore, the guidance instrumentation systematic error is separated from the vehicle trajectory measurement data. The measured data processing results show that the accuracy of the separation of guidance instrumentation systematic error based on PSO is better than that of the traditional Bayesian estimation and principal component estimation methods. The proposed method has practical engineering application value in vehicle test.
机译:提出了一种基于粒子群优化(PSO)的新型引导仪表系统误差的新分离方法。遥测环境函数矩阵严重病变,导致引导仪器系统误差分离的性能下降。在此,将引导仪器系统分离的问题转换为优化问题,并且PSO用于估计系统误差系数。此外,引导仪器系统误差与车辆轨迹测量数据分开。测量的数据处理结果表明,基于PSO的引导仪表系统误差分离的准确性优于传统的贝叶斯估计和主成分估计方法。该方法在车辆测试中具有实用的工程应用价值。

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