Abstract: The paper aims at the problem of nonlinear Gaussian system filtering with state constraints. In particle filtering, state vector is projected to the state constrained subspace via projection method, and the modified state vector is evaluated using the Lagrange multiplier method. Because either state estimation or particles can be modified in the particle filtering, two new methods are given to deal with particle filtering with equality state constraints. The filtering errors of the new methods are lower than the that of general particle filter obviously. Simulation results verify the effectiveness of the new methods.