000			01827 a2200229 4500
020			_a9789040719769
020			_a9040719764
040			_cIIT Kanpur
041			_aeng
082			_a511.35 _bT297d
100			_aTeunissen, P. J. G.
245			_aDynamic data processing _cP. J. G., Teunissen _brecursive least-squares
260			_bDelft Academic Press,VSSD _c2001 _aThe Netherlands
300			_a241p
440			_aSeries on mathematical geodesy and positioning
520			_aThis book is a follow-up on Adjustment theory. It extends the theory to the case of time-varying parameters with an emphasis on their recursive determination. Least-squares estimation will be the leading principle used. A least-squares solution is said to be recursive when the method of computation enables sequential, rather than batch, processing of the measurement data. The recursive equations enable the updating of parameter estimates for new observations without the need to store all past observations. Methods of recursive least-squares estimation are therefore particularly useful for applications in which the time-varying parameters need to be instantly determined. Important examples of such applications can be found in the fields of real-time kinematic positioning, navigation and guidance, or multivariate time series analysis. The goal of this book is therefore to convey the necessary knowledge to be able to process sequentially collected measurements for the purpose of estimating time-varying parameters. The theory is illustrated by means of many worked out examples. They are drawn from applications such as kinematic positioning, satellite orbit determination and inertial navigation
650			_aParameter estimation
650			_aTesting
650			_aGeodesy
650			_aRecursive functions
942			_cBK
999			_c561097 _d561097