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

2021 ◽  
Vol 13 (21) ◽  
pp. 4222
Author(s):  
Wei Huang ◽  
San Jiang ◽  
Wanshou Jiang
Keyword(s):  
Calibration Method ◽  
Satellite System ◽  
Bundle Adjustment ◽  
Self Calibration ◽  
Critical Configurations ◽  
Mathematical Formulas ◽  
Uav Images ◽  
Iterative Optimization Algorithm ◽  
Global Navigation Satellite ◽  
Camera Distortion

Camera self-calibration determines the precision and robustness of AT (aerial triangulation) for UAV (unmanned aerial vehicle) images. The UAV images collected from long transmission line corridors are critical configurations, which may lead to the “bowl effect” with camera self-calibration. To solve such problems, traditional methods rely on more than three GCPs (ground control points), while this study designs a new self-calibration method with only one GCP. First, existing camera distortion models are grouped into two categories, i.e., physical and mathematical models, and their mathematical formulas are exploited in detail. Second, within an incremental SfM (Structure from Motion) framework, a camera self-calibration method is designed, which combines the strategies for initializing camera distortion parameters and fusing high-precision GNSS (Global Navigation Satellite System) observations. The former is achieved by using an iterative optimization algorithm that progressively optimizes camera parameters; the latter is implemented through inequality constrained BA (bundle adjustment). Finally, by using four UAV datasets collected from two sites with two data acquisition modes, the proposed algorithm is comprehensively analyzed and verified, and the experimental results demonstrate that the proposed method can dramatically alleviate the “bowl effect” of self-calibration for weakly structured long corridor UAV images, and the horizontal and vertical accuracy can reach 0.04 m and 0.05 m, respectively, when using one GCP. In addition, compared with open-source and commercial software, the proposed method achieves competitive or better performance.

scholarly journals Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment

2019 ◽  
Vol 11 (4) ◽  
pp. 442 ◽  
Author(s):  
Zhen Li ◽  
Junxiang Tan ◽  
Hua Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Point Clouds ◽  
Calibration Method ◽  
Satellite System ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Self Calibration ◽  
Global Navigation Satellite ◽  
Mean Square Errors ◽  
Scanning Systems

Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.

scholarly journals The Use of SMAP-Reflectometry in Science Applications: Calibration and Capabilities

2019 ◽  
Vol 11 (20) ◽  
pp. 2442 ◽  
Author(s):  
Nereida Rodriguez-Alvarez ◽  
Sidharth Misra ◽  
Erika Podest ◽  
Mary Morris ◽  
Xavier Bosch-Lluis
Keyword(s):  
Global Navigation Satellite System ◽  
Incidence Angle ◽  
Calibration Method ◽  
Satellite System ◽  
High Gain ◽  
Navigation Satellite ◽  
Antenna Gain ◽  
Transmitted Power ◽  
High Gain Antenna ◽  
Global Navigation Satellite

The Soil Moisture Active Passive (SMAP) mission became one of the newest spaceborne Global Navigation Satellite System–Reflectometry (GNSS-R) missions collecting Global Positioning System (GPS) bistatic radar measurements when the band-pass center frequency of its radar receiver was switched to the GPS L2C band. SMAP-Reflectometry (SMAP-R) brings a set of unique capabilities, such as polarimetry and improved spatial resolution, that allow for the exploration of scientific applications that other GNSS-R missions cannot address. In order to leverage SMAP-R for scientific applications, a calibration must be performed to account for the characteristics of the SMAP radar receiver and each GPS transmitter. In this study, we analyze the unique characteristics of SMAP-R, as compared to other GNSS-R missions, and present a calibration method for the SMAP-R signals that enables the standardized use of these signals by the scientific community. There are two key calibration parameters that need to be corrected: The first is the GPS transmitted power and GPS antenna gain at the incidence angle of the measured reflections and the second is the convolution of the SMAP high gain antenna pattern and the glistening zone (Earth surface area from where GPS signals scatter). To account for the GPS transmitter variability, GPS instrument properties—transmitted power and antenna gain—are collocated with information collected from the CYclone Global Navigation Satellite System (CYGNSS) at SMAP’s range of incidence angles (37.3° to 42.7°). To account for the convolutional effect of the SMAP antenna gain, both the scattering area of the reflected GPS signal and the SMAP antenna footprint are mapped on the surface. We account for the size of the scattering area corresponding to each delay and Doppler bin of the SMAP-R measurements based off the SMAP antenna pattern, and normalize according to the size of a measurement representative to one obtained with an omnidirectional antenna. We have validated these calibration methods through an analysis of the coherency of the reflected signal over an extensive area of old sea ice having constant surface characteristics over a period of 3 months. By selecting a vicarious scattering surface with high coherency, we eliminated scene variability and complexity in order to avoid scene dependent aliases in the calibration. The calibration method reduced the dependence on the GPS transmitter power and gain from ~1.08 dB/dB to a residual error of about −0.2 dB/dB. Results also showed that the calibration method eliminates the effect of the high gain antenna filtering effect, thus reducing errors as high as 10 dB on angles furthest from SMAP’s constant 40° incidence angle.

scholarly journals Identifying Geomorphological Changes of Coastal Cliffs through Point Cloud Registration from UAV Images

2021 ◽  
Vol 13 (16) ◽  
pp. 3152
Author(s):  
Xiangxiong Kong
Keyword(s):  
Point Clouds ◽  
Satellite System ◽  
Small Scale ◽  
3D Point Clouds ◽  
Implementation Costs ◽  
Coastal Cliffs ◽  
Geomorphological Changes ◽  
Uav Images ◽  
Gps Devices ◽  
Global Navigation Satellite

Cliff monitoring is essential to stakeholders for their decision-making in maintaining a healthy coastal environment. Recently, photogrammetry-based technology has shown great successes in cliff monitoring. However, many methods to date require georeferencing efforts by either measuring geographic coordinates of the ground control points (GCPs) or using global navigation satellite system (GNSS)-enabled unmanned aerial vehicles (UAVs), significantly increasing the implementation costs. In this study, we proposed an alternative cliff monitoring methodology that does not rely on any georeferencing efforts but can still yield reliable monitoring results. To this end, we treated 3D point clouds of the cliff from different periods as geometric datasets and further aligned them into the same coordinate system using a rigid registration protocol. We examined the performance of our approach through a few small-scale experiments on a rock sample as well as a full-scale field validation on a coastal cliff. The findings of this study would be particularly valuable for underserved coastal communities, where high-end GPS devices and GIS specialists may not be easily accessible resources.

scholarly journals Evaluation of the Georeferencing Accuracy of a Photogrammetric Model Using a Quadrocopter with Onboard GNSS RTK

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2318 ◽  
Author(s):  
Martin Štroner ◽  
Rudolf Urban ◽  
Tomáš Reindl ◽  
Jan Seidl ◽  
Josef Brouček
Keyword(s):  
Vertical Component ◽  
Satellite System ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Control Points ◽  
Ground Sample ◽  
Ground Control Points ◽  
Aerial Vehicle ◽  
Global Navigation Satellite ◽  
Orientation Parameters

Using a GNSS RTK (Global Navigation Satellite System Real Time Kinematic) -equipped unmanned aerial vehicle (UAV) could greatly simplify the construction of highly accurate digital models through SfM (Structure from Motion) photogrammetry, possibly even avoiding the need for ground control points (GCPs). As previous studies on this topic were mostly performed using fixed-wing UAVs, this study aimed to investigate the results achievable by a quadrocopter (DJI Phantom 4 RTK). Three image acquisition flights were performed for two sites of a different character (urban and rural) along with three calculation variants for each flight: georeferencing using ground-surveyed GCPs only, onboard GNSS RTK only, and a combination thereof. The combined and GNSS RTK methods provided the best results (at the expected level of accuracy of 1–2 GSD (Ground Sample Distance)) for both the vertical and horizontal components. The horizontal positioning was also accurate when georeferencing directly based on the onboard GNSS RTK; the vertical component, however, can be (especially where the terrain is difficult for SfM evaluation) burdened with relatively high systematic errors. This problem was caused by the incorrect identification of the interior orientation parameters calculated, as is customary for non-metric cameras, together with bundle adjustment. This problem could be resolved by using a small number of GCPs (at least one) or quality camera pre-calibration.

scholarly journals COOPERATIVE LOCALISATION USING IMAGE SENSORS IN A DYNAMIC TRAFFIC SCENARIO

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 117-124
Author(s):  
P. Trusheim ◽  
Y. Chen ◽  
F. Rottensteiner ◽  
C. Heipke
Keyword(s):  
Linear Interpolation ◽  
Satellite System ◽  
Bundle Adjustment ◽  
Time Dependent ◽  
Automated Driving ◽  
Traffic Scenario ◽  
Normal Speed ◽  
Anchor Points ◽  
Global Navigation Satellite ◽  
Gnss Data

Abstract. Localisation is one of the key elements in navigation. Especially due to the development in automated driving, precise and reliable localisation becomes essential. In this paper, we report on different cooperation approaches in visual localisation with two vehicles driving in a convoy formation. Each vehicle is equipped with a multi-sensor platform consisting of front-facing stereo cameras and a global navigation satellite system (GNSS) receiver. In the first approach, the GNSS signals are used as excentric observations for the projection centres of the cameras in a bundle adjustment, whereas the second approach uses markers on the front vehicle as dynamic ground control points (GCPs). As the platforms are moving and data acquisition is not synchronised, we use time dependent platform poses. These time dependent poses are represented by trajectories consisting of multiple 6 Degree of Freedom (DoF) anchor points between which linear interpolation takes place. In order to investigate the developed approach experimentally, in particular the potential of dynamic GCPs, we captured data using two platforms driving on a public road at normal speed. As a baseline, we determine the localisation parameters of one platform using only data of that platform. We then compute a solution based on image and GNSS data from both platforms. In a third scenario, the front platform is used as a dynamic GCP which can be related to the trailing platform by markers observed in the images acquired by the latter. We show that both cooperative approaches lead to significant improvements in the precision of the poses of the anchor points after bundle adjustment compared to the baseline. The improvement achieved due to the inclusion of dynamic GCPs is somewhat smaller than the one due to relating the platforms by tie points. Finally, we show that for an individual vehicle, the use of dynamic GCPs can compensate for the lack of GNSS data.

scholarly journals Magnetometer heading estimation through online calibration for land navigation applications

2021 ◽  
Vol 2 (1) ◽  
pp. 56-69
Author(s):  
Muhammad Iqbal ◽  
Masood Ur Rehman ◽  
Umar Iqbal Bhatti ◽  
Najam Abbas Naqvi
Keyword(s):  
User Involvement ◽  
Field Testing ◽  
Calibration Method ◽  
Satellite System ◽  
Online Calibration ◽  
Magnetic Model ◽  
Magnetometer Calibration ◽  
Heading Estimation ◽  
Global Navigation Satellite ◽  
Calibration Techniques

For land navigation applications, the integration of the magnetometer with the combination of MEMS-INS and the Global Navigation Satellite System (GNSS) give excellent results. During land navigation applications, the magnetometer’s heading can also be used during the GNSS outages. The calibration of the magnetometer is indispensable to calculate its accurate heading. There exist several methods for magnetometer calibration. Some are offline and some are online calibration techniques. In this paper, a calibration method is proposed to estimate the magnetometer’s parameters through online calibration in run time. In this method, the reference magnetic field is calculated from the World Magnetic Model (WMM-2020). Moreover, reference roll, pitch and heading are provided from some other sources such as GNSS, Attitude Heading Reference System (AHRS), or reference INS. For different roll and pitch sectors, calibration parameters are estimated and stored. These parameters are used for magnetometer online calibration during the field testing. Both the headings obtained by the online calibration and conventional lab calibrations are analysed. Furthermore, the heading estimated through the online calibration is autonomous and fast. Subsequently, there is no user involvement in this online calibration technique and no specific movements to the device are provided. The heading obtained by novel technique is as accurate as obtained by conventional offline lab calibration.

scholarly journals ACCURATE ESTIMATION OF ORIENTATION PARAMETERS OF UAV IMAGES THROUGH IMAGE REGISTRATION WITH AERIAL OBLIQUE IMAGERY

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 599-605 ◽  
Author(s):  
F. A. Onyango ◽  
F. Nex ◽  
M. S. Peter ◽  
P. Jende
Keyword(s):  
Low Cost ◽  
Satellite System ◽  
Aerial Images ◽  
Measurement Unit ◽  
Accurate Estimation ◽  
Ratio Test ◽  
Uav Images ◽  
Global Navigation Satellite ◽  
The Impact ◽  
Orientation Parameters

Unmanned Aerial Vehicles (UAVs) have gained popularity in acquiring geotagged, low cost and high resolution images. However, the images acquired by UAV-borne cameras often have poor georeferencing information, because of the low quality on-board Global Navigation Satellite System (GNSS) receiver. In addition, lightweight UAVs have a limited payload capacity to host a high quality on-board Inertial Measurement Unit (IMU). Thus, orientation parameters of images acquired by UAV-borne cameras may not be very accurate.<br><br> Poorly georeferenced UAV images can be correctly oriented using accurately oriented airborne images capturing a similar scene by finding correspondences between the images. This is not a trivial task considering the image pairs have huge variations in scale, perspective and illumination conditions. This paper presents a procedure to successfully register UAV and aerial oblique imagery. The proposed procedure implements the use of the AKAZE interest operator for feature extraction in both images. Brute force is implemented to find putative correspondences and later on Lowe’s ratio test (Lowe, 2004) is used to discard a significant number of wrong matches. In order to filter out the remaining mismatches, the putative correspondences are used in the computation of multiple homographies, which aid in the reduction of outliers significantly. In order to increase the number and improve the quality of correspondences, the impact of pre-processing the images using the Wallis filter (Wallis, 1974) is investigated. This paper presents the test results of different scenarios and the respective accuracies compared to a manual registration of the finally computed fundamental and essential matrices that encode the orientation parameters of the UAV images with respect to the aerial images.

scholarly journals On the Calibration of GNSS-Based Vehicle Speed Meters

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 591 ◽  
Author(s):  
Adolfo Martucci ◽  
Giovanni Cerasuolo ◽  
Orsola Petrella ◽  
Marco Laracca
Keyword(s):  
Calibration Method ◽  
Satellite System ◽  
Wide Field ◽  
Vehicle Speed ◽  
Experimental Calibration ◽  
International Laboratory Accreditation Cooperation ◽  
Technical Requirements ◽  
Measurement Results ◽  
On The Road ◽  
Global Navigation Satellite

Thanks to their metrological characteristics (accuracy, dimensions, synchronization capability, easy interfacing, and so on), in the last few years, the GNSS (Global Navigation Satellite System) based speed instruments are often used in a wide field of application. The traceability of the measurement results achieved by the GNSS instrument should be made by means of calibration procedures in compliance with the ISO/IEC 17025 standard and ILAC (International Laboratory Accreditation Cooperation) policy on the traceability of measurement results. In this context, some calibration methodologies have been proposed in the literature or used by some calibration centers. In a speed range from 1 to 300 km/h, an analysis on the suitability of the experimental calibration method (based on a couple of photocells placed on the road at a certain distance) for the GNSS speed measurement systems is presented in this paper. An analysis of the measurement setup has allowed for the recognition of both all the uncertainty contributions and defines the variability range of their values. After the formulation of the relationships between the uncertainty contributions and the total calibration uncertainty due to the calibration method, the sensitivity analysis has been made. The analyzed measurement setup, even if considering a careful choice of both instrumentations and methodologies, is suitable for the calibration of high accuracy GNSS based instruments only considering distances between the photocells sufficiently large and for speed values lower than 200 km/h. In any case, the proposed analysis can be a useful tool to allow for the choices on the measurement setup to reach the desired trade-off between calibration costs and compliance with technical requirements and also the calibration of instrumentation different by GNSS.

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