Kalman-filter-aided correlation for parameter estimation

Sylvie G. Tonda; Jean-Pierre Huignard

doi:10.1117/12.279520

29 October 1997 Kalman-filter-aided correlation for parameter estimation

Sylvie G. Tonda, Jean-Pierre Huignard

Proceedings Volume 3163, Signal and Data Processing of Small Targets 1997; (1997) https://doi.org/10.1117/12.279520
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Parameter estimation can be performed by either optical/digital correlation techniques or digital adaptive filtering. For a three- dimensional estimation of parameters, the problem is difficult to solve with correlation techniques, essentially because the correlation of the observed image with all reference images of the database is not practically possible. We propose a solution based on Kalman filter-aided correlation. This reduces the number of required correlations. The parameter estimation resulting from the digital filtering is used as the a priori knowledge. The correlation of the observed image is then performed with a small number of correlation filters, selected from the a priori information. The a posteriori parameters are given by whichever of the selected correlation filters provides the maximum correlation function. The method is tested in the particular application of determining the 3-D attitude of maneuvering targets.

Citation Download Citation

Sylvie G. Tonda and Jean-Pierre Huignard "Kalman-filter-aided correlation for parameter estimation", Proc. SPIE 3163, Signal and Data Processing of Small Targets 1997, (29 October 1997); https://doi.org/10.1117/12.279520

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