Estimation theory, Kalman filtering
The Kalman filter is an important component of optimal estimation theory. It has applications in a wide range of high performance control systems including navigational, fire control, and targeting systems. The Kalman filter, however, has not been utilized to its full potential due to the limitations of its inherent computational intensiveness which requires “off-line” processing or allows only low bandwidth real-time applications.
The recent advances in VLSI circuit technology have created the opportunity to design algorithms and data structures for direct implementation in integrated circuits. A systolic architecture is a concept which allows the construction of massively parallel systems in integrated circuits and has been utilized as a means of achieving high data rates. A systolic system consists of a set of interconnected processing elements, each capable of performing some simple operation.
The design of a processing element in an orthogonal systolic architecture will be investigated using the state of the art in VLSI technology. The goal is to create a high speed, high precision processing element which is adaptive to a highly configurable systolic architecture. In order to achieve the necessary high computational throughput, the arithmetic unit of the processing element will be implemented using the Logarithmic Number System. The Systolic architecture approach will be used in an attempt to implement a Kalman filtering system with both a high sampling rate and a small package size. The design of such a Kalman filter would enable this filtering technology to be applied to the areas of process control, computer vision, and robotics.
Papadourakis, George M.
Master of Science (M.S.)
College of Engineering
Length of Campus-only Access
Masters Thesis (Open Access)
Condorodis, John P., "Design of a Processing Element for the Systolic Array Implementation of a Kalaman Filer" (1987). Retrospective Theses and Dissertations. 5028.