Title :
Mapping the Kalman tracking algorithm onto the transputer network
Author_Institution :
Sch. of Instrum. & Electron., Anna Univ., Chennai
fDate :
4/1/1998 12:00:00 AM
Abstract :
The Kalman tracking algorithm estimates position, velocity, and acceleration of a target from noisy measurement. A parallel Kalman algorithm is derived using the row-column partitioning with the modified state vector representation for multiprocessor realization. Mapping the tasks onto the multiprocessor system to minimize the time needed to complete all the tasks is an NP hard problem, and it arises when the task dependency structure of a parallel algorithm differs from the processor interconnection topology or when the number of processes generated by the algorithm exceeds the number of processors available. The efficient mapping of 3D-3S parallel Kalman tracking algorithm onto the network of 10 transputers, which are connected in tree structure that achieves a speedup of 6 is presented here
Keywords :
Kalman filters; computational complexity; parallel algorithms; parallel architectures; radar computing; radar signal processing; radar tracking; target tracking; tracking filters; transputer systems; 3D-3S algorithm; Kalman tracking algorithm; NP hard problem; efficient mapping; mapping onto transputer network; modified state vector representation; multiprocessor realization; noisy radar measurement; parallel Kalman algorithm; row-column partitioning; target acceleration; target position; target tracking filter; target velocity; task dependency structure; transputer arrays; tree structure; Acceleration; Accelerometers; Kalman filters; Multiprocessing systems; NP-hard problem; Parallel algorithms; Partitioning algorithms; Position measurement; Target tracking; Velocity measurement;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
