论文部分内容阅读
The classic state methods for trajectory estimation in boost phase with multi-range-rate system include method of point-by-point manner and that of spline-model-based manner.Both are deficient in terms of model-approximation accuracy and systematic error determination thus resulting in the estimation errors well beyond the requirements,especially,concerning the maneuvering trajectory.This article proposes a new high-precision estimation approach based on the residual error analysis.The residual error comprises three components,i.e.systematic error,model truncation error and random error.The approach realizes self-adaptive estimation of systematic errors in measurements following the theory of sparse representation of signals to minimize the low-frequency components of residual errors.By taking median-and high-frequency components as indexes,the spline model-approximation is improved by optimizing node sequence of the spline function and the weight selection for data fusion through iteration.Simulation has validated the performances of the proposed method.
The classic state methods for trajectory estimation in boost phase with multi-range-rate system include method of point-by-point manner and that of spline-model-based manner. Both are deficient in terms of model-approximation accuracy and systematic error determination thus resulting in the estimation errors well beyond the requirements, especially, concerning the maneuvering trajectory. This article proposes a new high-precision estimation approach based on the residual error analysis. The residual error comprises three components, iesystematic error, model truncation error and random error. The approach realizes self-adaptive estimation of systematic errors in measurements following the theory of sparse representation of signals to minimize the low-frequency components of residual errors. By taking median-and high-frequency components as indexes, the spline model- approximation is improved by optimizing node sequence of the spline function and the weight selection for data fusion through iter ation.Simulation has validated the performances of the proposed method.