Title :
Optimal measurement scheduling for prediction and estimation
Author :
Avitzour, Daniel ; Rogers, Steven R.
Author_Institution :
ELTA Electron. Ind., Ashdod, Israel
fDate :
10/1/1990 12:00:00 AM
Abstract :
A general theory of optimal measurement scheduling for least-squares estimation is developed. The theory is based on the assumption that the cost of a measurement is inversely proportional to the variance of measurement noise, and that it is possible to distribute the total measurement cost arbitrarily among a set of measurements. The theory leads to a nonquadratic minimization problem. An effective algorithm for solving this problem is developed. The theory is applied to the prediction of a discrete-time integrated Wiener process from noisy past samples
Keywords :
filtering and prediction theory; least squares approximations; minimisation; scheduling; signal processing; discrete-time integrated Wiener process; least-squares estimation; measurement cost; nonquadratic minimization problem; optimal measurement scheduling; signal processing; Additive noise; Costs; Energy measurement; Kalman filters; Least squares approximation; Noise measurement; Power measurement; Random variables; Signal processing; Signal to noise ratio;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
