Integrity is one of the most important parameters characterizing the Global Navigation Satellite Systems (GNSS) performance for safety-related applications. It is defined as a measure of trust to be placed in the correctness of the information supplied by the total system. This concept is more and more important, especially for applications in urban environment with standalone GNSS system, where GNSS performance is strongly degraded by the signal propagation conditions. Non line of Sight (NLOS) signals, caused by the surrounding obstacles, are of particular interest, as the error they induced remains a large cause of inaccuracy. In order to get rid of these constraints and to guarantee a better performance of positioning accuracy as well as integrity, several approaches can be used, such as positioning weighting models, 3D city models, Fault Detection and Exclusion (FDE) techniques etc. Since the concepts of integrity and accuracy are strongly related to each other, a better accuracy can help to improve the integrity performance. Thus, to reduce and to bound position errors are our two main objectives. In the work presented here, we will introduce 2 classes of methods which contribute to the NLOS signal mitigation as well as integrity performance. The first class concerns the use of different weighting models in order to reduce the influence of the NLOS on the overall measurements. The second class consists of Fault Detection and Exclusion (FDE) algorithms which allow users to identify and remove the outliers.