Robust estimate for exterior ballistic trajectory based on sparse parameters fusion modeling

The fusion with multi-measure data, such as optical measure, radar measure, and GPS and BDS data to estimate the exterior ballistic trajectory is a tendency for the high precise measure system in the current shooting range. However, the outlier and the model difference are inevitable commonly in these measure data, which will greatly influence the estimate precision. In this paper, the fusion measure model is presented, and then a robust estimate method to eliminate the outlier influence on the exterior ballistic trajectory is analyzed. Besides, the corresponding estimate algorithm and calculation steps based on robust estimate theory are established. Finally, the simulation calculation shows that the proposed method can effectively decrease the influence of the outlier and the model difference to the estimate precision. Compared with the traditional sparse parameter estimate method, this method is really effective.