Parallel implementation of radar tracking extended Kalman filters on transputer networks

The extended Kalman filter (EKF)used in radar tracking applications is computationally intensive leading to difficulties in broadband real-time applications. Hence, it is necessary to resort to parallel processing techniques. With the advent of very large scale integration (VLSI) technology, different types of architectures such as systolic arrays and wavefront arrays have been developed for this purpose. The transputer is one such architecture that can be used as a processing node in a parallel processing network. Therefore, two configurations, namely, pipe configuration and mesh configuration are developed for transputer implementation of radar tracking extended Kalman filtering. The EKF algorithm is analyzed in detail for reduction of number of computations. The transputer implementations are written using ANSI-C language with the proposed reduction of matrix operations and run using a mother board with 4 TRAMS each containing one T800 transputer. A typical maneuvering trajectory is simulated and used to compare the computation time per iteration of single and four transputer implementations of the tracking Kalman filter. Further, the speed-up comparison of sequential implementation of EKF, both with and without the proposed reduction of computations, is reported.<>