The passive sensors can only obtain angle information, and cannot obtain the location information of the target. Therefore, the target tracking of a single passive sensor is difficult to meet observability conditions. The thesis focuses on the expansion of the measurement of the single passive sensors Gaussian-Hermitian filtering, and establishes the multiple passive sensors Gaussian-Hermitian filtering model. A larger model error will be caused by the strong motorization due to that the Singer model is only applicable to the target motion within the range of the uniform and uniformly acceleration. Besides, normal truncated model is a better practical model which is essentially the nonzero mean time model, and can more truly reflect changes of motorized range and intensity of the target. The thesis based on normal truncated model proposes the dual passive sensors Gauss-Hermitian maneuvering target tracking algorithm of the angle measurement, and the simulation results show that the method is capable of stably tracking the maneuvering target.