Simulation and performance evaluation of a parallel architecture for signal processing

This paper presents an approach to implementing the parallel Kalman filter. The parallel Kalman filter is computationally intensive and hence complex due to the inherent matrix operations. Often, the filter cannot be computed in real time when the system has a large number of state variables. Discussed is a method for achieving almost real-time performance. In addition, a method for determining stability of the Kalman filter is presented. This method involves the use a paradigm that achieves high performance and close to real time results while maintaining accuracy for the Kalman filter. In addition, the paradigm shows an improvement of the processor utilization over other implementations and provides flexibility in terms of the hardware used for implementation.

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A Speed-Optimized Systolic Array Processor Architecture for Spatio-Temporal 2-D IIR Broadband Beam Filters

Madanayake

Bruton

2008

IEEE Trans. Circuits Syst. I

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Simulation and performance evaluation of a parallel architecture for signal processing

Cited by 4 publications

References 5 publications

Parallel image processing with the block data parallel architecture

Parallel image processing with the block data parallel architecture

Parallel processing and stability analysis of the Kalman filter

A Speed-Optimized Systolic Array Processor Architecture for Spatio-Temporal 2-D IIR Broadband Beam Filters

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