The invention relates to a multi-sensor quantitative fusion target tracking method based on a variational Bayesian method and a strong tracking information filtering method. According to the multi-sensor quantitative fusion target tracking method, a structure including a primary processor and a secondary processor are provided. In the primary processor, an enhanced measurement matrix H(k) and enhanced
global information z (upsilon, k) are constructed; one-step prediction (k|k)-1) and corresponding
covariance P(k|k-1) are calculated,
global information predication z (k|k-1) is calculated, and a z (upsilon, k, 1), the (k|k)-1 and the P(k / k-1) are sent into the secondary processor. In the secondary processor, information
noise variance is calculated, and (upsilon, k, 1) is sent to the primary processor, and in the primary processor, fusion
estimation and corresponding
covariance can be obtained through calculation, wherein please see the instruction for the formula of fusion
estimation and corresponding
covariance. Due to the fact that the variational Bayesian method and the self-adaptive strong tracking information filtering method are adopted in the multi-sensor quantitative fusion target tracking method, the high tracking capacity is achieved, unknown variance of
noise can be estimated and measured, and the self-adaptive function can be achieved. Meanwhile, an
attenuation coefficient can be estimated through an
iterative method without calculating a jacobian matrix.