Parallel Kalman filtering on the Connection Machine

Abstract

A parallel algorithm for square-root Kalman filtering has been developed and implemented on the Connection Machine (CM). Performance measurements show that the CM filter runs in time linear in the state vector size. This represents a great improvement over serial implementations, which run in cubic time. A specific multiple-target-tracking application in which several targets are to be tracked simultaneously, each requiring one or more filters, is considered. A parallel algorithm that, for fixed-size filters, runs in constant time, independently of the number of filters simultaneously processed, has been developed.<>