Sensing the terrain and using it for aiding the inertial navigation system has been widely used in air platforms since the 1960's. TERCOM and SITAN are well-known algorithms for sensing the terrain with a radar altimeter and calculating a correction for the navigation states according to a digital elevation map. In the absence of GPS signals, it is extremely important to be able to make positional fixes. In this paper, first we developed a simulation environment for a conceptual application of TAN (Terrain Aided Navigation) for land vehicles. Basically, the test platform is always on the ground so we can assume a trivial zero terrain clearance measurement and apply well-known TAN algorithms. With this new idea, an inertial measurement unit (IMU), a digital elevation map and a barometer are sufficient to apply the TAN algorithms in land vehicles. A widely used navigation aid in land navigation, odometer, is also considered in this TAN application. Error models are developed for each sensor and a dynamic model is used to simulate the IMU data of a land vehicle which moves on the terrain surface. A Kalman filter is designed to track navigation states and as a reference, truth model data is used to find the error statistics of the navigation states via Monte Carlo simulations. We also compare the simulation results with real time road test results. This paper finally discusses the requirements on the accuracy of sensors, digital maps and the vehicle capability. The vehicle has to be able to move on a land that has characteristic features for a successful application of the TAN algorithms.