This paper studies the application of several nonlinear filters for the problem of Mars entry navigation by using radiometric measurements from Mars orbiters and Mars Surface Beacons (MSBs). A suitable dynamic model of Mars entry is developed. The movement of MSBs due to Mars rotation is also considered in the measurement model. The performance of an Extended Kalman Filter (EKF), First-order Divided Difference Filter (DDF1), Unscented Kalman Filter (UKF), and Particle Filter (PF) is compared in terms of estimation capability and computation costs. The theoretical Cramer-Rao Lower Bound (CRLB) of estimation errors are derived for Mars entry to evaluate the performance of the filters. A consistency test is also carried out to verify the filters. In simulations, by the comparison of estimation errors, position and velocity Root Mean Square Error (RMSE), error standard deviation versus Square Root of CRLB (SR CRLB), credibility and computation time, it is concluded that DDF1 is preferred for Mars entry navigation.