Communications resources in modern automated systems have to be shared between different users and purposes. A process filtering task performed by a dedicated processor and integrating measurements delivered by a remote information source may in particular be subject to data flow limitations. The authors examine some problems related to these measurement data reductions in a linear filtering algorithm, focusing on linear observation compression schemes. A global approach gives a sufficient algebraic condition to admit reduced-order measurement vectors. Compression policies, dynamically optimized under specific criteria, are proposed. Remaining generic problems and possible extensions of such an approach are also discussed.
|Original language||English (US)|
|Title of host publication||Proceedings of the IEEE Conference on Decision and Control|
|Publisher||Publ by IEEEPiscataway, NJ, United States|
|Number of pages||6|
|State||Published - Dec 1 1991|