To avoid failing in visual tracking situation when employing single feature,a nonlinear target tracking method based on multi-feature fusion is proposed.Grey histogram is used to describe the overall distribution characteristics of the target and edge feature is employed to extract the high frequency details.The two algorithms are fused in the probabilistic model of particle filter.Feature reliability estimation based on half-band width and contribution is proposed,which provides more reliable features with more particles.In this way,the particle numbers of the features are adjusted dynamically.Compared with single-feature tracking method,the tracking result shows that the algorithm has the strong ability of tracking under local obstruction.The average tracking error of the new algorithm decreases by 0.5 pixels.