Name
Abstract | ||
|---|---|---|
In this paper we consider state estimation problems where there are multiple independent processses evolving but the estimation scheme can only select a limited set of processes to measure at each time step. Within a Gauss-Markov framework, we show the optimality of a scheduling scheme under various scenarios. These types of problems are common in sensor scheduling applications. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICIF.2006.301677 | 2006 9TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4 |
Keywords | Field | DocType |
sensor scheduling, Kalman filter, state estimation | Mathematical optimization,Fair-share scheduling,Computer science,Scheduling (computing),Two-level scheduling,Kalman filter,Gaussian process,Rate-monotonic scheduling,Dynamic priority scheduling,Round-robin scheduling | Conference |
Citations | PageRank | References |
1 | 0.80 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Craig O. Savage | 1 | 1 | 0.80 |
| Barbara F. La Scala | 2 | 54 | 11.26 |
| Bill Moran | 3 | 141 | 23.49 |