Iterative methods for parameter estimation
MacHardy, William R.
Therrien, Charles W.
MetadataShow full item record
Starting with a least squares formulation of the parameter estimation problem, both fixed data and data-adaptive iterative algorithms are developed. We apply two new techniques, namely diagonal perturbation and multiple partitioning, to existing finite impulse response (FIR) and infinite impulse response (IIR) fixed data matrix splitting algorithms, resulting in improved performance. Also, we extend the fixed data algorithms to the data-adaptive case, and contrast them with FIR and IIR recursive least squares (RLS) algorithms. Computer simulations are used to evaluate the computational effectiveness of the new algorithms. We show the general rate of convergence for the algorithms, evaluate their ability to correctly represent the spectral components of simulated system frequency response in noise, and present system performance, when the order of the model is chosen to be larger than the known system order (over-modeling).
Approved for public release; distribution is unlimited.
Showing items related by title, author, creator and subject.
Taylor, James G.; Neta, Beny (Monterey, California. Naval Postgraduate School, 2001-09); NPS-MA-01-001The goal of this study effort was to assess the ability of the Joint Conflict and Tactical Simulation (JCATS) to simulate the capabilities of non- lethal weapons (NLW) and to provide a product that can be incorporated into ...
Tappe, J.; Kim, J.J.; Jordan,A.; Agrawal, B.N. (2011);This paper presents a study of star tracker attitude estimation algorithms and implementation on an indoor ground-based Three Axis Spacecraft Simulator (TASS). Angle, Planar Triangle, and Spherical Triangle algorithms are ...
De Kooter, Peter M. (Monterey, California. Naval Postgraduate School, 1997-03);As part of the existing acoustic transient localization program, a feasibility study was performed to apply existing algorithms to signals at higher carrier frequencies. The coherent matching, autocorrelation matching and ...