## 1 Introduction
In addition, a higher elevation angle and SNR do not necessarily indicate fewer multipath effects in urban canyons. Thus, one needs to distinguish direct signals from multipath-corrupted signals and allocate different weights depending on the severity of the multipath effect. [PERSON] et al. [8] enhanced the ambiguity fixing success rate and reduced noise in position estimates by collecting SNR values over extended observation intervals, normalizing these values, and incorporating the results into stochastic modeling. However, their approach focuses primarily on the correlation between average SNR values and satellite elevation angles, without considering epoch-to-epoch fluctuations in SNR. [PERSON] et al. [9] addressed multipath effects in positioning by detecting multipath-impacted satellites in real time. Their method normalizes the C/N0 values based on elevation angle and processes each navigation satellite constellation individually. Although this normalization is applied on a per-satellite basis, the underlying statistical model is derived from datasets collected under open-sky conditions. Consequently, its effectiveness on mobile platforms in urban areas, where buildings of varying heights often obstruct satellite visibility, remains limited. [PERSON] et al. [10] improved positioning accuracy by incorporating the standard deviation of the SNR, measured over an arbitrary period, alongside the variances obtained during the estimation process. Specifically, if the standard deviation falls below a predefined threshold, the corresponding satellite is excluded from the positioning solution. However, in urban canyon environments, where the number of visible satellites is often significantly reduced, discarding additional satellites might make continuous positioning infeasible. [PERSON] et al. [11] reviewed various satellite exclusion methods, such as applying SNR thresholds based on elevation angle [12], using the fluctuation range of C/N0 over a specified duration [13], and employing residuals generated during the positioning process [14], comparing their respective advantages and disadvantages. In [11], the threshold is determined by analyzing a continuous time series of C/N0 values. If the C/N0 value drops below this threshold, the corresponding satellite signal is excluded from the positioning solution for a certain period, even if subsequent C/N0 values exceed the threshold. Nevertheless, this approach is inherently limited in that it may further reduce the number of available satellites, which is particularly problematic in urban canyon environments [10]. In this study, we developed a novel weight model to enhance GPS positioning integrity in urban canyons, where the multipath signal excessively interferes with the direct satellite signal. First, the SNR variability and its repeatability according to the receiver type and three distinctive signal reception environments were analyzed. Based on these results, a new weight model was devised based on an exponential function of SNR variability. The signals were separated into direct and non-direct based on their fluctuation patterns and given different weights. Finally, the developed model was validated in various environments, and time-sequential positioning accuracies were evaluated to demonstrate its integrity and continuity.