The robustness of the Sandia Inertial Terrain‐Aided Navigation (SITAN) algorithm has a pivotal influence on underwater vehicles' Gravity‐Aided Inertial Navigation Systems (GAINS). An abrupt glitch of the accuracy of the GAINS will evolve into a disaster when vehicles pass through areas of smooth gravity. In order to resolve vulnerability issues of initial error and linearization error, we propose the Correlation SITAN algorithm with Weight‐Reducing Iteration Technique (CSITAN + WRIT), in which the correlation process equals Terrain Contour Matching (TERCOM). The CSITAN algorithm is a Multipoint‐based Extended Kalman Filtering (MEKF) method, which can work in real time. First, we need to derive the state equation and observation equation of the Multipoint‐based SITAN algorithm based on the principle of the traditional SITAN algorithm. Then the accuracy of the state prediction can be improved, and the linearization error can be reduced by the correlation method based on TERCOM. Finally, the WRIT is utilized to reduce the possible influence of gross errors existing in the results of the MEKF and to extract a value with higher precision. The experimental results show that CSITAN + WRIT can achieve better accuracy and higher success rate of matching and can improve the possibilities of the occurrence of large matching errors than traditional SITAN methods in areas with smooth gravity. Copyright © 2017 Institute of Navigation

Defects and vertical short-wave irregularities significantly influence the maintenance of the railway tracks and the train safety, and hence, they need to be detected and eliminated in the early stages of formation. We studied the principles and algorithms to detect the defects and to measure the vertical shortwave irregularities by using a fiber optical gyroscope and an odometer, and the associated software was also developed. The principles of deformation index, namely, the ratio of angular rate to velocity and the method to determine the threshold of defects detection, are expatiated. The influence of the transfer function in measuring the vertical irregularities has long been a tough issue. The relation between the characteristics of deformation index and the wavelength of irregularities is studied by converting the deformation index from the time domain to the spatial domain. The post-processing module utilizes the results of the spectrum analysis of the deformation index to determine the wavelength of the track irregularities and eliminate the influence of the transfer function. To improve the accuracy of the calculation results, we analyzed the characteristics of the output of the gyroscope and the odometer and designed a series of targeted error-elimination methods. The forward and reverse dead-reckoning method is utilized to reduce the error accumulation, especially a high frequency noise when calculating the magnitude of the vertical short-wave irregularities. The experimental results show that the repeatability is 0.038 mm when the chord length is 1 m and 0.65 mm when the chord length is 10 m. The accuracy is 0.05 mm when compared with the results obtained using a ruler of 1 m. The moving speed of the instrument was approximately 0.6-1.2 m/s during the experiment. Both the accuracy and the efficiency can fulfill the requirements for the measurement of the short-wave irregularities.INDEX TERMS Fiber optical gyro, short-wave irregularity, deformation index, transfer function, dead reckoning.CUIJUN DONG received the B.E. degree in surveying and mapping engineering from the Uni-

When performing the inspection of subway tunnels, there is an immense amount of data to be collected and the time available for inspection is short; however, the requirement for inspection accuracy is high. In this study, a mobile laser scanning system (MLSS) was used for the inspection of subway tunnels, and the key technology of the positioning and orientation system (POS) was investigated. We utilized the inertial measurement unit (IMU) and the odometer as the core sensors of the POS. The initial attitude of the MLSS was obtained by using a static initial alignment method. Considering that there is no global navigation satellite system (GNSS) signal in a subway, the forward and backward dead reckoning (DR) algorithm was used to calculate the positions and attitudes of the MLSS from any starting point in two directions. While the MLSS passed by the control points distributed on both sides of the track, the local coordinates of the control points were transmitted to the center of the MLSS by using the ranging information of the laser scanner. Then, a four-parameter transformation method was used to correct the error of the POS and transform the 3-D state information of the MLSS from a navigation coordinate system (NCS) to a local coordinate system (LCS). This method can completely eliminate a MLSS’s dependence on GNSS signals, and the obtained positioning and attitude information can be used for point cloud data fusion to directly obtain the coordinates in the LCS. In a tunnel of the Beijing–Zhangjiakou high-speed railway, when the distance interval of the control points used for correction was 120 m, the accuracy of the 3-D coordinates of the point clouds was 8 mm, and the experiment also showed that it takes less than 4 h to complete all the inspection work for a 5–6 km long tunnel. Further, the results from the inspection work of Wuhan subway lines showed that when the distance intervals of the control points used for correction were 60 m, 120 m, 240 m, and 480 m, the accuracies of the 3-D coordinates of the point clouds in the local coordinate system were 4 mm, 6 mm, 7 mm, and 8 mm, respectively.