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This paper investigates different linear and non-linear state estimation techniques applicable in the scenario of unmanned air vehicle platform with an image sensor that attempts to navigate in a known urban terrain. Feature detection and matching steps are carried out using DTCWT (Dual tree Complex Wavelet Transform) descriptor. The state parameters of the vehicle are subsequently estimated using the measurements from the image sensor. Due to the non-linear nature of the problem, non-linear filters such as particle filters are often used. Various other methods have been proposed in the literature to the problem ranging from linear Kalman filter to non-linear probabilistic based techniques. This paper therefore attempts to study different state estimation methods and understand two main approaches in particular the Kalman and particle filter for the problem.