This project presents the design and development of a multidimensional Kalman filter with the purpose to estimate the tri-dimensional position of a stationary object based on GPS measurements. Because this is not the only filtering algorithm available, a comparison with other four types of filters (one-dimensional optimal Kalman algorithm, quasi-optimal stationary Kalman algorithm, simple moving average algorithm and optimally unbiased moving average algorithm) is also developed.