指挥控制与仿真2017，Vol.39Issue(5)：109-112,133,5.DOI:10.3969/j.issn.1673-3819.2017.05.023
最小二乘及其改进算法在外测数据处理中的应用
The Application of Least Squares and its Improved Algorithm in Measured Data Post-processing
牟志华 1郭枫1
作者信息
- 1. 解放军91550部队94分队, 辽宁 大连 116023
- 折叠
摘要
Abstract
The classical Least Squares algorithm is limited in measured data post-processing. This paper discusses the ques-tion of least square estimate for multi-radar nonlinear model by importing Jacobi matrix, adopts Bayes estimate for the meas-ured data with prior information, uses ridge estimation formula to resolve design matrix multiple correlations of measured da-ta. For different test project and measured data with all kinds of errors, fit formula should be chosen bases the factof meas-ured data. This paper provides a new way to the application of Least Squares and its improved algorithm in measured data post-processing.关键词
最小二乘/改进算法/数据处理/Bayes估计Key words
least squares/improved algorithm/data processing/Bayes estimate分类
天文与地球科学引用本文复制引用
牟志华,郭枫..最小二乘及其改进算法在外测数据处理中的应用[J].指挥控制与仿真,2017,39(5):109-112,133,5.
