## 2 Related Works  
Recently, using 3D building model as aiding information to mitigate or exclude the multipath and NLOS effects has become a popular topic of study. The metric of NLOS signal exclusion using an elevation-enhanced map, extracted from a 3D map, is developed and tested using real vehicular data [21]. An extended idea of identifying NLOS signals using infrared camera set at an automotive vehicle was suggested [22]. The potential of using a dynamic 3D map to design a multipath exclusion filter for a vehicle-based tightly-coupled GPS/INS integration system was studied in [14]. A forecast satellite visibility based on a 3D urban model to exclude NLOS signals in urban areas was developed in [15]. The above approaches aim to exclude the NLOS signal; however, the exclusion is very likely to cause a horizontal dilution of precision (HDOP) distortion scenario, due to the blockage of buildings along the two sides of streets. In other words, the lateral positioning error would be much larger than that of the along track direction. As a result, approaches that applied multipath and NLOS signals as measurements become essential. The shadow matching method uses 3D building models to predict the satellite visibility and to compare it with measured satellite visibility to improve the cross street positioning accuracy [19]. NLOS delay estimation by a 3D map-based particle filter, which is used in this paper, was proposed and tested in with dynamic pedestrian experiments [23, 24]. The benefit of the quasi-zenith satellite system (QZSS) L1-submeter-class augmentation with integrity function (L1-SAIF) and the rising of the multi-GNSS to the 3D map-based positioning method are evaluated [25, 30], respectively.  
RAIM is a GPS receiver self-checking algorithm for the fault of navigation solution based on redundant measurements and proposed by [28]. RAIM is well-known for its capability of detecting the error caused by mis-modeling. As a result, researchers from Stanford University proposed applying weighted RAIM to capture mis-modeling of ionospheric and satellite orbit/clock corrections [31]. A detailed algorithm and simulation of RAIM availability is released by Imperial College University [32]. Recently, the intention of using RAIM to deal with multipath and NLOS effect is increased. A scenario of only five GPS satellites in view is studied to increase the availability of RAIM [33]. A consistency checking algorithm using RAIM concept is developed to mitigate the multipath effects [34]. Toyota ITS team also releases a report to show the effeteness of RAIM to exclude multipath range error for vehicle application [35]. Discussions of using multi-GNSSs RAIM, including GPS/GLONASS/Beidou/QZSS, are described in [36]. In 2015, a simulation result of multiple fault exclusion with large number of pseudorange measurements is released, showing its capability in the area with high probability of measurement fault [37]. This multiple fault exclusion based on L1 norm minimization [38] is promising to exclude strong multipath effects and NLOS reception. It is very interesting to evaluate this multiple fault exclusion algorithm in the previous proposed 3D map pedestrian positioning method. This RAIM multiple fault detection algorithm is expected to exclude the abnormal NLOS signal. Thus, it is the objective of this paper.