Single observer passive target tracking based on adaptive gene H∞ filter is proposed for the highly non-linear passive location and tracking system, which means that tracking filters often failed to catch and keep tracking of the emitter. On the basis of sigma point transformation technique and H∞ filtering method, the proposed algorithm can decrease linearization error of high nonlinear system and solve the noise uncertainty problem. The algorithm has a control abnormal innovations, which can efficiently restrain the unfavorable influence out of outliers, and apply the scaled factor and a fading factor to adjust the distance of sampling-point to center-point and the covariance matrix of estate predict error. And then the problem of non-local effects of sampling can be resolved and single observer passive target tracking system is more robust to measurement error of time difference of arrival: Simulation results show that the proposed algorithm is similar to sigma point H∞ filtering method in computational complexity, and the algorithm outperforms the sigma point H∞ filtering method in tracking accuracy as stability. Therefore it is more suitable to the nonlinear state estimation.