The means to track objects in 3D space is paramount to computer vision and robotics. Improving upon prior work of the M.A.R.S. project enabled more accurate object tracking and ranging, required investigation into current techniques of stereo depth estimation, object tracking algorithms and the use of FPGA platforms. The research focused on aviation, ground vehicle and robotic applications of stereo computer vision and image processing methods. The implementation of the project design focused on how to obtain greater disparity resolution from the stereo system while minimizing memory resources. The analysis of the optimal method and then the coding and debugging of the optimal solution was performed to insure inter-operability with the existing system and lay the foundation for further expansion of the system. Comparative analysis of Xilinx FPGA platforms and MATLAB simulation of the concept provided data on hardware resources, improved disparity output and the minimal use of memory.