## 1 Introduction  
With the wide utilization of satellite navigation technology, the integrity of navigation solutions has become a major issue, especially for safety-of-life applications [1; 2; 3]. Receiver autonomous integrity monitoring (RAIM) is essential for a GPS receiver, which is developed to assess the integrity of the received GPS signals and provide a timely warning message to the user in the presence of a failure. As an approach and landing phase is a typical part of a flight path with unsafe incidents, designing a suitable RAIM procedure is especially important to guarantee flight safety. Normally, the performance of RAIM relies on a sufficient number of visible satellites and a fine geometrical configuration to check the consistency of the measurements. However, since the approach and landing phase is usually consistent with low GPS visibility conditions due to obstructions, there is a larger mask angle leading to insufficient visible satellites and a poor geometrical configuration. Consequently, the availability and fault detection performance of RAIM will decrease dramatically [4; 5; 6]. Therefore, it is essential to further investigate the RAIM methods in the approach and landing phase. When the satellite measurements are insufficient, the conventional RAIM method will not be able to meet the stringent navigation performance requirements in the approach and landing phase. To solve this problem, a logical idea is to bring other aids to provide additional measurements for RAIM. In recent decades, additional navigation devices such as barometric altimeter, inertial navigation system, and other satellite constellations have been considered. For example, the vertical ranging of a barometric altimeter is applied to enrich the navigation measurements for RAIM augmentation [7]. However, the accuracy of the barometric altimeter is susceptible to the quickly atmospheric pressure change, which is very common in the approach and landing phase. With the speeds and attitudes provided by an inertial navigation system (INS), [PERSON] _et al._ established the Kalman equations of integrated INS/GPS to improve the performance of RAIM [8], while the error of the INS may drift over the time and contaminate the integrity result. Inspired by the traditional random sample consensus (RANSAC) algorithm in pattern recognition, [PERSON] _et al._ designed the range consensus (RANCO) algorithm to improve the multi-fault detection result with the assistance of other constellations [9]. Although the RANCO algorithm performs well with sufficient satellites in the simulation, many parameters need to be set empirically. More recently, some augmented RAIM methods without using additional navigation devices are also investigated. [PERSON] _et al._ proposed a new receiver clock bias prediction model based on the discrete grey model to design the clock-aided RAIM method [10], while some factors upon the receiver clock bias series are uncertain. The map-aided integrity method has been investigated for use in intelligent transportation systems [11]. Unfortunately, the performance of availability has not been improved, as the map-aided method gives the user an alert and changes to an alternative navigation system once GPS is unavailable. Considering these deficiencies above, it is essential to research on utilizing other measurement sources to aid RAIM in approach and landing phase. In this paper, a vision-aided RAIM (VA-RAIM) is proposed to improve the performance of integrity monitoring. As the satellite measurements are insufficient due to the obstructions, our basic idea is to introduce the landmarks, photographed by a vision system, as the pseudo-satellites to enrich the navigation measurements. To aid RAIM, however, the vision measurements applied for RAIM should be accurate and reliable. Although the existing computer vision technologies perform well in vision information extraction, the vision measurements inevitably incur errors due to background interference and platform dithering.