Camera auto-calibration in GPS/INS/stereo camera integrated kinematic positioning and navigation system

Abstract

This paper presents a novel two-step camera calibration method in a GPS/INS/Stereo Camera multi-sensor kinematic positioning and navigation system. A camera auto-calibration is first performed to obtain for lens distortion parameters, up-to-scale baseline length and the relative orientation between the stereo cameras. Then, the system calibration is introduced to recover the camera lever-arms, and the bore-sight angles with respect to the IMU, and the absolute scale of the camera using the GPS/INS solution. The auto-calibration algorithm employs the three-view scale-restraint equations (SRE). In comparison with the collinearity equations (COL), it is free from landmark parameters and ground control points (GCPs). Therefore, the proposed method is computationally more efficient. The results and the comparison between the SRE and COL methods are presented using the simulated and road test data. The results show that the proposed SRE method requires less computation resources and is able to achieve the same or better accuracy level than the traditional COL.

Camera Self-Calibration with GNSS Constrained Bundle Adjustment for Weakly Structured Long Corridor UAV Images

“…Since the constraints between the long corridor structure are reduced to the minimum, the correlation of camera intrinsic parameters and external parameters cannot be restricted with the stability structure of images, which leads to the "bowl effect" phenomenon and affects the relative and absolute accuracy of 3D reconstruction. At present, most UAVs are equipped with centimeter-level high-precision differential GNSS, which can provide better initial position parameters to constrain the camera projection centers [33,34]. Traditional technology for fusing high-precision GNSS locations and oriented images of SfM is to minimize a weighted sum of image and GNSS errors.…”