- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
A Novel Tilt Correction Technique for Irradiance Sensors and Spectrometers On-Board Unmanned Aerial Vehicles
摘要： In unstable atmospheric conditions, using on-board irradiance sensors is one of the only robust methods to convert unmanned aerial vehicle (UAV)-based optical remote sensing data to reflectance factors. Normally, such sensors experience significant errors due to tilting of the UAV, if not installed on a stabilizing gimbal. Unfortunately, such gimbals of sufficient accuracy are heavy, cumbersome, and cannot be installed on all UAV platforms. In this paper, we present the FGI Aerial Image Reference System (FGI AIRS) developed at the Finnish Geospatial Research Institute (FGI) and a novel method for optical and mathematical tilt correction of the irradiance measurements. The FGI AIRS is a sensor unit for UAVs that provides the irradiance spectrum, Real Time Kinematic (RTK)/Post Processed Kinematic (PPK) GNSS position, and orientation for the attached cameras. The FGI AIRS processes the reference data in real time for each acquired image and can send it to an on-board or on-cloud processing unit. The novel correction method is based on three RGB photodiodes that are tilted 10° in opposite directions. These photodiodes sample the irradiance readings at different sensor tilts, from which reading of a virtual horizontal irradiance sensor is calculated. The FGI AIRS was tested, and the method was shown to allow on-board measurement of irradiance at an accuracy better than ±0.8% at UAV tilts up to 10° and ±1.2% at tilts up to 15°. In addition, the accuracy of FGI AIRS to produce reflectance-factor-calibrated aerial images was compared against the traditional methods. In the unstable weather conditions of the experiment, both the FGI AIRS and the on-ground spectrometer were able to produce radiometrically accurate and visually pleasing orthomosaics, while the reflectance reference panels and the on-board irradiance sensor without stabilization or tilt correction both failed to do so. The authors recommend the implementation of the proposed tilt correction method in all future UAV irradiance sensors if they are not to be installed on a gimbal.
关键词： unmanned aerial vehicle,UAV,irradiance,reflectance factor,tilt stabilization,drone
更新于2025-09-23 15:23:52
-
Impact paint sensor based on polymer/multi-dimension carbon nano isotopes composites
摘要： We presented a novel impact paint sensor made of piezoresistive nano-carbon composites and studied its characteristics. The paint sensors were fabricated with multi-walled carbon nanotube (MWCNT), exfoliated graphite nano-platelets (xGnP), and a hybrid type of the two nano-carbon fillers and were sprayed onto a carbon fiber reinforced plastic (CFRP) panel for lab testing. In ball drop impact test, the MWCNT-xGnP-based hybrid sensor showed the best characteristics in impact energy sensing within the range 0.07-1.0J. We also studied the piezoresistive mechanism due to dimensional variations of nano carbon isotopes for sensor design. Piezorestivity of nano-carbon sensor was significantly dominated the electrical contact variation of the electrical fillers in a matrix. This study is expected to provide a feasibility test for designing impact paint sensors with optimized sensitivity for a composite structural health monitoring (SHM).
关键词： Carbon nanotube (CNT),Exfoliated graphite nanoplate (xGnP),Structural health monitoring (SHM),Unmanned aerial vehicle (UAV),Impact paint sensor
更新于2025-09-23 15:22:29
-
[IEEE 2018 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia) - Chengdu, China (2018.10.26-2018.10.30)] 2018 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia) - Wireless Power Transfer for 3D Printed Unmanned Aerial Vehicle (UAV) Systems
摘要： Unmanned aerial vehicles (UAVs) have attracted a lot of attention for various applications such as service delivery, pollution mitigation, farming, and rescue operations over the past few years. However, the short duration of battery and the inconvenience of changing it is always a problem. Basically, small UAVs can only carry very limited payloads otherwise the battery will be drained more frequently. This project presents an automatic and high-efficient wireless power transfer (WPT) to supply a 3D printed UAV. A UAV has been 3D printed with wireless power transfer kit implemented to charge 3S 1500 mAh Li-Po battery with up to 1000 mAh automatically once it is landed, without manual operation. 24V DC is supplied to the transmitting side of WPT with the operating frequency at 180kHz and once the battery is fully charged, the charging process will also stop automatically.
关键词： Unmanned Aerial Vehicle (UAV),Wireless Power Transfer,3D Printing
更新于2025-09-23 15:22:29
-
Successive DSPE-based coherently distributed sources parameters estimation for unmanned aerial vehicle equipped with antennas array
摘要： In electronic countermeasures and reconnaissance, unmanned aerial vehicle (UAV) has played a more and more significant role. Usually when UAV conducts low altitude reconnaissance, due to the complicated environment, the reflected signals of the same source through different propagation paths will produce multipath signals. In this paper, we construct the received multipath signals of UAV with antennas array as coherently distributed (CD) sources model and propose a successive distributed signal parameter estimation (S-DSPE) algorithm to estimate its nominal direction of arrival (DOA) and angular spread. The proposed algorithm simplifies two-dimensional (2D) spectral peak searching within the conventional DSPE algorithm to one-dimensional spectral peak searching, which remarkably reduces the computational complexity of conventional DSPE algorithm. Furthermore, the parameters estimation performance of the proposed algorithm is close to the conventional DSPE algorithm, and outperforms the estimation of signal parameters via rotational invariance technique (ESPIRT) algorithm and propagator method(PM). The simulations results verify the usefulness of the proposed algorithm.
关键词： Distributed signal parameter estimation (DSPE),Nominal direction of arrival (DOA),Coherently distributed(CD),Unmanned aerial vehicle (UAV)
更新于2025-09-23 15:21:21
-
A UAV-Mounted Free Space Optical Communication: Trajectory Optimization for Flight Time
摘要： In this work, we address the trajectory optimization of a fixed-wing unmanned aerial vehicle (UAV) using free space optical communication (FSOC). Here, we focus on maximizing the flight time of the UAV by considering practical constraints for wireless UAV communication, including limited propulsion energy and required data rates. We find optimized trajectories in various atmospheric environments (e.g., moderate-fog and heavy-fog conditions), while also considering the channel characteristics of FSOC. In addition to maximizing the flight time, we consider the energy efficiency maximization and operation-time minimization problem to find the suboptimal solutions required to meet those constraints. Furthermore, we introduce a low-complexity approach to the proposed framework. In order to address the optimization problem, we conduct a bisection method and sequential programming and introduce a new feasibility check algorithm. Although our design considers suboptimal solutions owing to the nonconvexity of the problems, our simulations indicate that the proposed scheme exhibits a gain of approximately 44.12% in terms of service time when compared to the conventional scheme.
关键词： trajectory design,Free space optical communication (FSOC),wireless communications with an unmanned aerial vehicle (UAV),flight time maximization,UAV-mounted FSOC
更新于2025-09-12 10:27:22
-
NRLI-UAV: Non-rigid registration of sequential raw laser scans and images for low-cost UAV LiDAR point cloud quality improvement
摘要： Accurate registration of light detection and ranging (LiDAR) point clouds and images is a prerequisite for integrating the spectral and geometrical information collected by low-cost unmanned aerial vehicle (UAV) systems. Most registration approaches take the directly georeferenced LiDAR point cloud as a rigid body, based on the assumption that the high-precision positioning and orientation system (POS) in the LiDAR system provides sufficient precision, and that the POS errors are negligible. However, due to the large errors of the low-precision POSs commonly used in the low-cost UAV LiDAR systems (ULSs), dramatic deformation may exist in the directly georeferenced ULS point cloud, resulting in non-rigid transformation between the images and the deformed ULS point cloud. As a result, registration may fail when using a rigid transformation between the images and the directly georeferenced LiDAR point clouds. To address this problem, we proposed NRLI-UAV, which is a non-rigid registration method for registration of sequential raw laser scans and images collected by low-cost UAV systems. NRLI-UAV is a two-step registration method that exploits trajectory correction and discrepancy minimization between the depths derived from structure from motion (SfM) and the raw laser scans to achieve LiDAR point cloud quality improvement. Firstly, the coarse registration procedure utilizes global navigation satellite system (GNSS) and inertial measurement unit (IMU)-aided SfM to obtain accurate image orientation and corrects the errors of the low-precision POS. Secondly, the fine registration procedure transforms the original 2D-3D registration to 3D-3D registration. This is performed by setting the oriented images as the reference, and iteratively minimizing the discrepancy between the depth maps derived from SfM and the raw laser scans, resulting in accurate registration between the images and the LiDAR point clouds. In addition, an improved LiDAR point cloud is generated in the mapping frame. Experiments were conducted with data collected by a low-cost UAV system in three challenging scenes to evaluate NRLI-UAV. The final registration errors of the images and the LiDAR point cloud are less than one pixel in image space and less than 0.13 m in object space. The LiDAR point cloud quality was also evaluated by plane fitting, and the results show that the LiDAR point cloud quality is improved by 8.8 times from 0.45 m (root-mean-square error [RMSE] of plane fitting) to 0.05 m (RMSE of plane fitting) using NRLI-UAV, demonstrating a high level of automation, robustness, and accuracy.
关键词： Low-cost,Light detection and ranging (LiDAR),Unmanned aerial vehicle (UAV),Image sequence,Non-rigid registration
更新于2025-09-11 14:15:04
-
[IEEE 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Hangzhou (2018.8.6-2018.8.9)] 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Research on Empirical Model and Gap Rate Model for Estimating Rice Leaf Area Index Based on UAV HD Digital Images
摘要： The Leaf Area Index (LAI), as an important plant characteristic parameter, is of great significance for the monitoring of vegetation growth and the estimation of surface vegetation productivity. Rice is one of the world's major food crops, timely and accurate measurement of rice LAI can provide scientific information on agriculture. The remote sensing system of UAV is characterized by its cost-effective and real-time data acquisition. The method of estimating LAI by remote sensing technology has great advantages over traditional methods and has gradually become a frontier method for agricultural research. At present, the commonly used LAI inversion methods are empirical model method and physical model method. The former is not accurate because not all of the spectral information is used. The latter cannot directly calculate the analytical solution because of the complicated model and many input parameters. The main purpose of this paper is to obtain high-definition digital images of different varieties of rice using low-altitude drones, and to analyze the feasibility of estimating the LAI of rice canopy by empirical model method and porosity model method, and analyze the difference and estimation process between them. There are problems.
关键词： Leaf Area Index(LAI),Remote sensing,Empirical model,Unmanned Aerial Vehicle(UAV),Rice,Gap rate model
更新于2025-09-11 14:15:04
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - GPU Acceleration of UAV Image Splicing Using Oriented Fast and Rotated Brief Combined with PCA
摘要： In this study, an accelerating method of oriented FAST and rotated BRIEF combined with principal component analysis (ORB/PCA) is proposed for splicing detection of unmanned aerial vehicle (UAV) images. Compared to traditional scale-invariant feature transform (SIFT) and speeded up robust features (SURF) methods, the proposed ORB/PCA can not only be faster but also produce more accurate. Moreover, in order for the proposed ORB to be effective for image stitching process in near real-time, the Compute Unified Device Architecture (CUDA) application programming interface of graphics processing unit (GPU) is cooperated to speed up the proposed method. Experimental results show that the proposed GPU based ORB/PCA framework is suitable for splicing detection of UAV images in Earth remote sensing. It can improve the image stitching process both in time and accuracy compared to conventional methods.
关键词： oriented FAST and rotated BRIEF (ORB),principal component analysis (PCA),unmanned aerial vehicle (UAV),graphics processing unit (GPU)
更新于2025-09-09 09:28:46