In urban canyons, smartphone users experienced great inconvenience in inaccurate GNSS positioning. The development of 3D mapping aided (3DMA) GNSS is regarded as one solution for this challenge. Several ideas in 3DMA GNSS are proposed including, 1) non-light-of-sight (NLOS) measurement exclusion based on the 3D building model, 2) GNSS shadow matching, 3) ray-tracing based 3DMA GNSS, 4) likelihood-based 3DMA GNSS, etc. Recently, researches show the integration of these 3DMA GNSS methods can enhance the positioning accuracy. For example, GNSS shadow matching integrates with likelihood-based approach can reach a performance of less than 10 meters in most urban areas of cities. However, the performance of this state-of-the-art method is not as satisfactory in the deep urban canyons of mega Asian cities such as Hong Kong. In deep urban canyons, the number of NLOS affected measurements became excessive. About 75% of total measurement could be affected by NLOS. To achieve 10 meters level of positioning performance, the NLOS measurement must be corrected. Ray-tracing based 3DMA GNSS aims to correct the pseudorange delay caused by NLOS reflection. It is proven effective in the urban canyons in Tokyo, Japan. However, its computation load is immense. We proposed a skymask (which is the skyplot with building boundaries) aided NLOS correction method, which can be regarded as an accelerated ray-tracing 3DMA GNSS method. Instead of using this skymask method standalone, this paper integrates the state-of-the-art 3DMA GNSS with our proposed skymask aided method. According to the experiment results, the NLOS correction generated by the skymask method further improves the performance of the integration of GNSS shadow matching and likelihood based method.