Three-dimensional attitude estimation and tracking by multicorrelation technique with normalized optimal trade-off filters

We introduce a three-dimensional target attitude estimation method based on the linear optimal filtering and the signal processing prediction algorithms. By estimating the three- dimensional attitude and the scale of the target, we are able to predict the temporal trajectory of the target and to perform a robust tracking. Most cases of parameter estimation with the help of correlation deal with the two- dimensional estimation of position, scale and object rotation. Treating a three-dimensional parameter estimation problem leads to an increase in the number of correlation filters. We propose a strategy to reduce the number of correlations and thus reduce the computational burden and the processing time. We demonstrate the efficiency of the strategy in the case of optimal trade-off filters.