Parallelization of the Kalman filter for banded systems on multicore computational platforms

Parallel implementation of the Kalman filter (KF), with emphasis on multicore architecture implementation is investigated. It is shown that KF provides enough parallelizm to achieve linear speedup in the number of cores used. A computationally efficient implementation that exhibit good scalability properties is presented. The implementation is based on the assumption of a banded system matrix. Both time-varying and invariant systems can be generally transformed to a realization with a banded system matrix. An analysis of the algorithm that provides guidelines to the choice of implementation hardware to meet a desired performance is also given.