Adaptive sensing of target signature with unknown amplitude
Document Type
Conference Proceeding
Publication Date
12-1-2008
Abstract
The problem of selecting the optimal linear measurement, subject to energy constraints, for nonlinear parameter estimation is stated. While the problem is similar to previously reported measurement selection problems for Gaussian random vectors, there are some key differences stemming from the fact that the signal amplitude is a nuisance parameter. An objective function based on minimizing the Bayesian Cramer-Rao bound is proposed. Through a linearization of the response vector and other simplifying assumptions, the objective function is reduced to a oneparameter function that is easily maximized. Simulation results comparing the optimal measurement to the traditional measurement suggest the potential for significantly improved estimator performance, although the linearization assumption is problematic when the parameter being estimated has a large prior variance. © 2008 IEEE.
Publication Title
Conference Record - Asilomar Conference on Signals, Systems and Computers
Recommended Citation
Fuhrmann, D.
(2008).
Adaptive sensing of target signature with unknown amplitude.
Conference Record - Asilomar Conference on Signals, Systems and Computers, 218-222.
http://doi.org/10.1109/ACSSC.2008.5074395
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/10290