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Parallel Algorithms and Architectures for Optimal State Estimation
November 1985 (vol. 34 no. 11)
pp. 1061-1068
J.H. Graham, Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute
Optimal state estimation procedures, such as the Kalman-Bucy filter, require a high-speed parallel implementation to fully realize their potential. This correspondence first analyzes and restructures these equations based on an expression tree representation. The resulting equations are then simulated on three proposed SIMD architectures (rectangular systolic array, linear array, and quad-clustered tree array) and evaluated for speedup, efficiency, and utilization as compared to a known serial implementation. Results are presented which graphically show the design tradeoffs between these architectures.
Index Terms:
state estimation, Kalman-Bucy filter, parallel processing, performance improvement, SIMD architectures
Citation:
J.H. Graham, T.F. Kadela, "Parallel Algorithms and Architectures for Optimal State Estimation," IEEE Transactions on Computers, vol. 34, no. 11, pp. 1061-1068, Nov. 1985, doi:10.1109/TC.1985.1676540
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