The need for accurate 3D spatial information is growing rapidly in many of today’s key industries, such as precision agriculture, emergency management, infrastructure monitoring, and defense. Unmanned aerial vehicles (UAVs) equipped with global navigation satellite systems/inertial navigation systems (GNSS/INS) and consumer-grade digital imaging sensors are capable of providing accurate 3D spatial information at a relatively low cost. However, with the use of consumer-grade sensors, system calibration is critical for accurate 3D reconstruction. In this study, ‘consumer-grade’ refers to cameras that require system calibration by the user instead of by the manufacturer or other high-end laboratory settings, as well as relatively low-cost GNSS/INS units. In addition to classical spatial system calibration, many consumer-grade sensors also need temporal calibration for accurate 3D reconstruction. This study examines the accuracy impact of time delay in the synchronization between the GNSS/INS unit and cameras on-board UAV-based mapping systems. After reviewing existing strategies, this study presents two approaches (direct and indirect) to correct for time delay between GNSS/INS recorded event markers and actual time of image exposure. Our results show that both approaches are capable of handling and correcting this time delay, with the direct approach being more rigorous. When a time delay exists and the direct or indirect approach is applied, horizontal accuracy of 1–3 times the ground sampling distance (GSD) can be achieved without either the use of any ground control points (GCPs) or adjusting the original GNSS/INS trajectory information.

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with frame and/or line cameras are used for a variety of applications. Geometric system calibration is crucial for delivering accurate products from UAV-based imaging systems. This paper presents automated geometric calibration strategies for UAV-based frame and line camera systems to estimate accurate system calibration parameters without the need for GCPs or manual measurements of tie points. The matching strategy used in this study to establish conjugate features among overlapping frame camera images is based on a traditional Structure from Motion (SfM) technique augmented with several layers of matching outlier removal. On the other hand, a new strategy relying on ortho-rectified images is introduced for automated feature matching in line camera scenes. Then, a general bundle adjustment (BA) procedure with system calibration capabilities for frame and line cameras is presented, where the derived automated tie points are used for estimating accurate geometric system calibration parameters. The proposed approach is evaluated using four datasets-two datasets captured by frame cameras and two datasets captured by line cameras. The results show that the developed automated calibration strategy is capable of producing the same level of absolute accuracy when compared to using manually-measured tie points for both frame camera and line camera systems. Results also indicate that the presented automated system calibration approach can be applied to systems even with significant deviation of actual system parameters from their nominal values, and still produce accurate estimates of calibration parameters. Index Terms-Image matching, system calibration, RGB frame cameras, hyperspectral line cameras, unmanned aerial vehicles (UAVs), integrated global navigation satellite system/inertial navigation system (GNSS/INS).

Unmanned aerial vehicles (UAVs ) equipped with imaging sensors and integrated global navigation satellite system/inertial navigation system (GNSS/INS ) units are used for numerous applications. Deriving reliable 3D coordinates from such UAVs is contingent on accurate geometric calibration, which encompasses the estimation of mounting parameters and synchronization errors. Through a rigorous impact analysis of such systematic errors, this article proposes a direct approach for spatial and temporal calibration (estimating system parameters through a bundle adjustment procedure) of a GNSS/INS -assisted pushbroom scanner onboard a UAV platform. The calibration results show that the horizontal and vertical accuracies are within the ground sampling distance of the sensor. Unlike for frame camera systems, this article also shows that the indirect approach is not a feasible solution for pushbroom scanners due to their limited ability for decoupling system parameters. This finding provides further support that the direct approach is recommended for spatial and temporal calibration of UAV pushbroom scanner systems.

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