New Calibration Method Using Low Cost MEM IMUs to Verify the Performance of UAV-Borne MMS Payloads

Chiang, Kai-Wei; Tsai, Meng Lun; Naser, El Sheimy; Habib, Ayman; Chu, Chih‐Ping

doi:10.3390/s150306560

Cited by 29 publications

(18 citation statements)

References 13 publications

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“…There are many studies describing the pre-calibration of digital cameras used for UAS mapping purposes during the last decade, and only a few with the camera mounted on a UAS and at a long object distance during calibration process. Some of them have been calibrated using planar calibration objects [13][14][15][16], some using a 3D target, but at short object distance [17][18][19], and only a few tested the impact of camera pre-calibration on UAS mapping projects [10,20].…”

Section: Related Workmentioning

confidence: 99%

3D Calibration Test-Field for Digital Cameras Mounted on Unmanned Aerial Systems (UAS)

2018

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Due to the large number of technological developments in recent years, UAS systems are now used for monitoring purposes and in projects with high precision demand, such as 3D model-based creation of dams, reservoirs, historical monuments etc. These unmanned systems are usually equipped with an automatic pilot device and a digital camera (photo/video, multispectral, Near Infrared etc.), of which the lens has distortions; but this can be determined in a calibration process. Currently, a method of “self-calibration” is used for the calibration of the digital cameras mounted on UASs, but, by using the method of calibration based on a 3D calibration object, the accuracy is improved in comparison with other methods. Thus, this paper has the objective of establishing a 3D calibration field for the digital cameras mounted on UASs in terms of accuracy and robustness, being the largest reported publication to date. In order to test the proposed calibration field, a digital camera mounted on a low-cost UAS was calibrated at three different heights: 23 m, 28 m, and 35 m, using two configurations for image acquisition. Then, a comparison was made between the residuals obtained for a number of 100 Check Points (CPs) using self-calibration and test-field calibration, while the number of Ground Control Points (GCPs) variedand the heights were interchanged. Additionally, the parameters where tested on an oblique flight done 2 years before calibration, in manual mode at a medium altitude of 28 m height. For all tests done in the case of the double grid nadiral flight, the parameters calculated with the proposed 3D field improved the results by more than 50% when using the optimum and a large number of GCPs, and in all analyzed cases with 75% to 95% when using a minimum of 3 GCP. In this context, it is necessary to conduct accurate calibration in order to increase the accuracy of the UAS projects, and also to reduce field measurements.

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Section: Related Workmentioning

confidence: 99%

3D Calibration Test-Field for Digital Cameras Mounted on Unmanned Aerial Systems (UAS)

2018

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“…This entails estimation of three translations and three rotations in the general case, similarly as in the multiple GNSS antenna case in Lee et al [3] and Hong et al [4]. Examples of this include Chiang et al [8] and Lobo and Dias [9]. Montalbano and Humphreys [10] compared lever-arm compensation by an extended Kalman filter (EKF) to multiple-model Kalman filters and a neural network, finding that the EKF outperformed the other methods.…”

Section: Introductionmentioning

confidence: 99%

GNSS-antenna lever arm compensation in aided inertial navigation of UAVs

Stovner

Johansen

2019

2019 18th European Control Conference (ECC)

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This paper considers aided inertial navigation of unmanned aerial vehicles aided with position measurements from one or more global navigation satellite system antennas, where the exact positions of the antennas are assumed unknown. This reflects that the antennas' location relative to the inertial sensor, i.e. the lever arms, might be difficult to measure accurately in the coordinate frame of the inertial sensor. Using inaccurate lever arm values will deteriorate both the position and attitude estimates of the vehicle. It is easier to manually and accurately measure the distances from each antenna to the inertial sensor and between antennas, and this information can be used constructively to estimate the lever arms online. In this paper, the distance information is used to reduce the representation of one or more lever arms to two or three states, respectively. An error-state extended Kalman filter is derived and compared to two other similar filters in simulations: one filter in which the lever arms are known and one which represents all lever arms as body-fixed positions. The suggested filter is shown to perform as well as the latter, but with a significantly smaller state space representation.

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“…Despite the fact that portability is a key factor in the current success of these devices, it comes with restrictions on the admissible payload [6]: this implies a careful election of the instrumentation mounted in the UAV. In particular, positioning and navigation are typically achieved by using lightweight Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical System (MEMS)-embedded sensors (i.e., integrated use of GNSS and the Inertial Navigation System (INS) [7,8]…”

Section: Introductionmentioning

confidence: 99%

“…In these cases, Direct Georeferencing (DG) is typically considered instead [25][26][27][28][29][30], i.e., the direct estimation of camera position and orientation with sensors mounted on the UAV (e.g., GNSS and INS). Motivated by the above considerations, DG has attracted the attention of several research groups in the last few years: inexpensive and lightweight sensor solutions are typically considered [25,28], where DG positioning accuracy is usually mainly related to the performance of the consumer-grade GNSS receiver in the integrated Position and orientation System (PoS) (e.g., ∼5 m [6,28]), whereas higher grade GNSS receivers can allow better positioning accuracy [31]). Similarly to DG, here, 3D reconstruction is obtained without using control points: in order to make the system usable even when GNSS is not available, UWB positioning is used instead.…”

Section: Introductionmentioning

confidence: 99%

A Low Cost UWB Based Solution for Direct Georeferencing UAV Photogrammetry

2017

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Thanks to their flexibility and availability at reduced costs, Unmanned Aerial Vehicles (UAVs) have been recently used on a wide range of applications and conditions. Among these, they can play an important role in monitoring critical events (e.g., disaster monitoring) when the presence of humans close to the scene shall be avoided for safety reasons, in precision farming and surveying. Despite the very large number of possible applications, their usage is mainly limited by the availability of the Global Navigation Satellite System (GNSS) in the considered environment: indeed, GNSS is of fundamental importance in order to reduce positioning error derived by the drift of (low-cost) Micro-Electro-Mechanical Systems (MEMS) internal sensors. In order to make the usage of UAVs possible even in critical environments (when GNSS is not available or not reliable, e.g., close to mountains or in city centers, close to high buildings), this paper considers the use of a low cost Ultra Wide-Band (UWB) system as the positioning method. Furthermore, assuming the use of a calibrated camera, UWB positioning is exploited to achieve metric reconstruction on a local coordinate system. Once the georeferenced position of at least three points (e.g., positions of three UWB devices) is known, then georeferencing can be obtained, as well. The proposed approach is validated on a specific case study, the reconstruction of the façade of a university building. Average error on 90 check points distributed over the building façade, obtained by georeferencing by means of the georeferenced positions of four UWB devices at fixed positions, is 0.29 m. For comparison, the average error obtained by using four ground control points is 0.18 m.

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New Calibration Method Using Low Cost MEM IMUs to Verify the Performance of UAV-Borne MMS Payloads

Cited by 29 publications

References 13 publications

3D Calibration Test-Field for Digital Cameras Mounted on Unmanned Aerial Systems (UAS)

3D Calibration Test-Field for Digital Cameras Mounted on Unmanned Aerial Systems (UAS)

GNSS-antenna lever arm compensation in aided inertial navigation of UAVs

A Low Cost UWB Based Solution for Direct Georeferencing UAV Photogrammetry

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