The final target representation model was obtained by means of linear fusing the two feature models, and the fusion coefficient was determined adaptively by contrast ratio of feature likelihood map.
并将两种特征模型进行线性融合，得到最终的目标表征模型，其中的融合系数由特征似然图对比度自适应确定。
The Kalman Filter is widely applied in the Information Fusion at the present, which can get the optimal estimate in the Linear-Gaussian model, but not applied in the nonlinear and non-Gaussian model.
目前在信息融合领域广泛使用的融合算法是卡尔曼滤波，它在线性高斯模型下能得到最优估计，但在非线性非高斯模型下则无法应用。
The Kalman Filter is widely applied in the Information Fusion at the present, which can get the optimal estimate in the Linear-Gaussian model, but not applied in the nonlinear and non-Gaussian model.
目前在信息融合领域广泛使用的融合算法是卡尔曼滤波，它在线性高斯模型下能得到最优估计，但在非线性非高斯模型下则无法应用。
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