In 1960, R.E. Kalman published his famous paper describing a recursive solution
to the discrete-data linear filtering problem. Since that time, due in large part to advances
in digital computing, the Kalman filter has been the subject of extensive research
and application, particularly in the area of autonomous or assisted
navigation.
In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata
linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital
computing, the
Kalman filter
has been the subject of extensive research and application,
particularly in the area of autonomous or assisted navigation. A very “friendly” introduction to the
general idea of the Kalman filter can be found in Chapter 1 of [Maybeck79], while a more complete
introductory discussion can be found in [Sorenson70], which also contains some interesting
historical narrative.
in this paper,wo propose an extension of the zerotree-based space-frequency quantization algorithm by adding a wedgelet symbol to its tree-pruning optimization.
