OPTIMIZATION OF AN ADAPTIVE KALMAN FILTER BASED ON INFORMATION-THEORY

An adaptive Kalman filter is described which can be optimized, even if the location of the required overlap-free region is not known a prior i. The optimization is based on maximizing the information yield from the filter procedure, and the results with the highest precision and a ccuracy are found when the information is at a maximum. The informatio n-based optimization is also used to demonstrate that more precise fil tering is accomplished with higher point densities, and that an optima l filter window exists, depending on the spectral resolution and the s ampling frequency. Simulations based on a grid search and on simplex o ptimization give similar results.