The computations involved in Kalman filter algorithms are highly structured with regular matrix-type operations. Moreover, Kalman filter algorithms can be specified as a set of parallel passes rearranged to be the type of the Fadeev algorithms for generalizing matrix/vector manipulations. Based on that, and in order to further improve the speed of updating the state estimate of Kalman filter equations and taking full advantage of the two parallel pipeline structures, a new combined SIMD/MISD (Single Instructions Multiple Data stream/ Multiple Instructions Single Data stream) Transputer implementation scheme is presented. This configuration has expanded the utilization of the twodimensional systolic architecture and significantly improved the speed of updating the state estimate and resulted in a significant saving in processing time complexity compared to SIMD transputer implementation.

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