Real-time Kinematic Research Articles

Structural Characteristics and Formation Mechanism of the Earth Fissures as a Geohazard in Birjand, Iran

Earth fissure structures are a common type of geohazard associated with geotechnical surface ruptures that can occur almost anywhere on the ground surface due to a variety of different mechanisms, and in most cases, these hazardous cracks have resulted in severe damage to infrastructure. Investigation of the structural characteristics of fissures in an active tectonic area (such as Birjand in eastern Iran) can improve our understanding of connections between the fissures and structural geology. The first reported earth fissures in NW Birjand are distributed along the North Birjand fault. Field observations and analysis of the detailed topography cross-sections using the real-time kinematic (RTK) technique have been used to infer the fissure development. Morphometric analysis of faults and fissures shows that the long axis of most fissure structures is distributed perpendicular to the strike of the North Birjand fault. The average volume strain in the study area was calculated to be 14.68 percent based on fissure geometry studies, with the maximum volume strain corresponding to the location of the North Birjand fault’s youngest splay. This splay formed fault-propagation folds with exposed fissure structures. This study shows that the fault-propagation folds in this system are subjected to the activity and evolution of the ground fissure as a result of the expansion of tensile stress.

Rice row tracking control of crawler tractor based on the satellite and visual integrated navigation

To achieve autonomous navigation of the crawler tractor in the paddy field, a set of control system was developed by integrating the satellite and visual navigation. The system is mainly composed of a satellite module, a visual module and a controller. The satellite module detects the deviation information between the tractor’s position and the pre-set line AB using GPS Real–time Kinematic (RTK) technology and the navigation is achieved according to the preview point tracking algorithm. The visual module obtains the rice crop images in real time by camera, and the binary image segmentation is completed by ExG(2G-R-B), Otsu and mask method. Then the region search algorithm is used to classify the region of each rice row, and the visual navigation path is fitted by the weighted least square method, and the weight value is based on the lookahead distance. Finally, the preview point tracking algorithm is used to realize the visual navigation. Furthermore, the control division line between the satellite navigation and visual navigation is established, the threshold value of which is determined based on the crop row deviation due to the satellite navigation when rice crops were planted. The crawler tractor navigation tests were conducted to evaluate the performance of the integrated navigation system. When the speed of the tractor was 0.4∼0.6 m/s, 0.7∼0.9 m/s and 1.0∼1.2 m/s, the maximum lateral deviation of the tracking by visual navigation was 0.18 m, 0.15 m and 0.14 m, respectively, and the RMSE was 55 mm, 64 mm and 60 mm, respectively. Under the same speed, when the threshold value was set to 0.15 m, the maximum lateral offset of the tracking by integrated navigation was 0.14 m, 0.13 m and 0.12 m, respectively, and the RMSE was 41 mm, 50 mm and 55 mm, respectively. The experimental results indicate that the satellite navigation module in the integrated navigation system functions well in rice row tracking when some seedlings are missing, and significantly reduces the navigation deviation and the degree of deviation fluctuation.

Overlap influence in images obtained by an unmanned aerial vehicle on a digital terrain model of altimetric precision

ABSTRACT Photogrammetric data are systematically used in several segments. Products such as Digital Terrain Models (DTMs) provide detailed surface information, however the geometric reliability of these products is questionable compared to data collected by topographic survey by GNSS RTK. The present research assesses the quality of DTMs obtained using an Unmanned Aerial Vehicle (UAV) with different parameters, overlap percentages, and flight directions, comparing the results to those of the topography method Global Navigation Satellite System – Real-Time Kinematic (GNSS RTK). Were done twelve flight plans with different overlaps (90x90, 80x80, 80x60, 70x50, 70x30, and 60x40%) and directions (transverse and longitudinal to the planting line). The parameters of height (Above Ground Land- AGL) and speed were fixed at 90 m and 3 m/s respectively and a Ground Sample Distance (GSD) of 0,1 m is obtained for all flights. Overall, the flight with 70x50% overlap in the transverse direction generated the best results, with a total processing time of 12 minutes and 17 seconds (about 1.5 hours faster than 90x90%), an Root Mean Square Error (RMSE) 0.589 m, and meets the minimum overlap required by 60X30% aerophotogrammetry; furthermore, the results did not differ statistically from the high overlaps of 90x90% and 80x80%.

Principle and performance of multi-frequency and multi-GNSS PPP-RTK

PPP-RTK which takes full advantages of both Real-Time Kinematic (RTK) and Precise Point Positioning (PPP), is able to provide centimeter-level positioning accuracy with rapid integer Ambiguity Resolution (AR). In recent years, with the development of BeiDou Navigation Satellite System (BDS) and Galileo navigation satellite system (Galileo) as well as the modernization of Global Positioning System (GPS) and GLObal NAvigation Satellite System (GLONASS), more than 140 Global Navigation Satellite System (GNSS) satellites are available. Particularly, the new-generation GNSS satellites are capable of transmitting signals on three or more frequencies. Multi-GNSS and multi-frequency observations become available and can be used to enhance the performance of PPP-RTK. In this contribution, we develop a multi-GNSS and multi-frequency PPP-RTK model, which uses all the available GNSS observations, and comprehensively evaluate its performance in urban environments from the perspectives of positioning accuracy, convergence and fixing percentage. In this method, the precise atmospheric corrections are derived from the multi-frequency and multi-GNSS observations of a regional network, and then disseminated to users to achieve PPP rapid AR. Furthermore, a cascade ambiguity fixing strategy using Extra‐Wide‐Lane (EWL), Wide-Lane (WL) and L1 ambiguities is employed to improve the performance of ambiguity fixing in the urban environments. Vehicle experiments in different scenarios such as suburbs, overpasses, and tunnels are conducted to validate the proposed method. In suburbs, an accuracy of within 2 cm in the horizontal direction and 4 cm in the vertical direction, with the fixing percentage of 93.7% can be achieved. Compared to the GPS-only solution, the positioning accuracy is improved by 87.6%. In urban environments where signals are interrupted frequently, a fast ambiguity re-fixing can be achieved within 5 s. Moreover, multi-frequency GNSS signals can further improve the positioning performance of PPP-RTK, particularly in the case of small amount of observations. These results demonstrate that the multi-frequency and multi-GNSS PPP-RTK is a promising tool for supporting precise vehicle navigation.

Weed Management in Ridge Tillage Systems—A Review

Although different modifications of ridge tillage (RT) systems exist in different regions around the world, the positive impacts of RT on crop yields and weed management are quite similar. This review gives a comprehensive summary of different forms of RT and highlights the benefits of RT for crop growth, mainly due to better access to soil moisture, nutrients and light. In temperate areas, RT can accelerate crop emergence because soil temperature is usually higher on the ridge. These stimulating effects increase crop competitiveness against weeds especially in the early period of crop development until canopy closure. RT with crops placed on the top of ridges can also be used for automatically guiding inter-row hoes and intra-row band sprayers. The ridges can replace automatic vision control systems for hoeing and band spraying, which are needed for precise weeding in conventional flat seedbeds. Therefore, RT can be considered a possible platform for smart/robotic weeding. This paper introduces a new RT system using real-time kinematic (RTK) global satellite navigation systems (GNSS) for the ridging and seeding of maize and soybean on top of recompacted ridges. Straight ridges with precise positioning data were used to guide mechanical weeding elements precisely along the crop rows. Simultaneously, weeds in the valleys were suppressed by living mulches. Field experiments with this new technology in maize showed 85.5% weed dry biomass suppression compared to an untreated control and a slightly higher weed control efficacy than mechanical weeding in flat seedbeds.

Behavior of Low-Cost Receivers in Base-Rover Configuration with Geodetic-Grade Antennas.

The main goal of this research was to evaluate the performances of the ZED-F9P-Ublox low-cost GNSS receiver in a base-rover real configuration. We realized a base configuration with two permanent stations based on the ZED-F9P and two geodetic antennas and the rover configuration based on another ZED-F9P and an ANN-MB-00-00 Multi-band (L1, L2/E5b/B2I) active GNSS u-blox antenna. In the calculation of the reference stations, we compared the solutions with the ZED-F9P receiver and a professional receiver. Comparison showed greater variability in the solutions, but the coordinate values were in very good agreement. Standard deviations were in the order of a few millimeters. On the rover side, two car tests were performed in two different environments, one in an extra-urban environment with a long baseline of approximately 30 km in an open sky area with varying visibility and shielded locations, the other one in an urban area around a circle approximately 10 km in diameter with the presence of buildings and open sectors. The results of the measurements were very good, with more than 95% of fixed solutions in real-time and a time to fix on reacquisition of 1 or 2 s. Moreover, real-time kinematic solutions were in good agreement with the post-processed ones, showing that less than 5% of differences were above 30 mm in the horizontal component and 100 mm in the vertical component.

A modified between‐receiver single‐difference‐based fault detection and exclusion algorithm for real‐time kinematic positioning

With the increasing number of available satellites from multi-global navigation satellite systems (GNSS) and their applications in complicated environments, an increased number of faults in measurements are inevitable. Fault detection and exclusion (FDE) is an effective way to reject observation faults in order to guarantee the integrity of a GNSS positioning and navigation system. We propose a modified between-receiver single-differencing (SD)-based FDE algorithm for real-time kinematic (RTK) positioning. First, a modified between-receiver SD model-based FDE is proposed for testing the estimated float ambiguities. This is helpful in rejecting observations with unreliable float ambiguities and obtaining reliable double-differencing (DD) integer ambiguities, denoted as the SD float model in the sequel. Second, DD ambiguities are resolved by the DD model and used to update the previous SD float ambiguity. After that, a modified SD fix model, taking the DD ambiguities as the known parameters, is further developed to detect any unreliable or fault-resolved ambiguities. To verify the modified SD model-based FDE algorithm, a kinematic vehicle test is conducted. The fault detection test statistics of the SD float model and the SD fix model, time-to-first-fix, ambiguity-fix rate, SD residuals, and positioning performances are examined. The results show that the modified FDE method can detect and exclude fault satellites accurately and effectively, which is verified by the SD residuals of fault satellites. The ambiguity-fix rate of the proposed modified FDE algorithm is improved by approximately 3% with 70 more epochs of fixes. Regarding the 3D positioning performance, the modified proposed SD-based FDE algorithm can achieve 54.11%, 57.78%, and 73.11% improvements for standard deviation, root mean square, and mean bias, respectively, when compared with the processing strategy without the use of the proposed FDE.

Farm Vehicle Following Distance Estimation Using Deep Learning and Monocular Camera Images.

This paper presents a comprehensive solution for distance estimation of the following vehicle solely based on visual data from a low-resolution monocular camera. To this end, a pair of vehicles were instrumented with real-time kinematic (RTK) GPS, and the lead vehicle was equipped with custom devices that recorded video of the following vehicle. Forty trials were recorded with a sedan as the following vehicle, and then the procedure was repeated with a pickup truck in the following position. Vehicle detection was then conducted by employing a deep-learning-based framework on the video footage. Finally, the outputs of the detection were used for following distance estimation. In this study, three main methods for distance estimation were considered and compared: linear regression model, pinhole model, and artificial neural network (ANN). RTK GPS was used as the ground truth for distance estimation. The output of this study can contribute to the methodological base for further understanding of driver following behavior with a long-term goal of reducing rear-end collisions.

M2DGR: A Multi-Sensor and Multi-Scenario SLAM Dataset for Ground Robots

We introduce M2DGR: a novel large-scale dataset collected by a ground robot with a full sensor-suite including six fish-eye and one sky-pointing RGB cameras, an infrared camera, an event camera, a Visual-Inertial Sensor (VI-sensor), an inertial measurement unit (IMU), a LiDAR, a consumer-grade Global Navigation Satellite System (GNSS) receiver and a GNSS-IMU navigation system with real-time kinematic (RTK) signals. All those sensors were well-calibrated and synchronized, and their data were recorded simultaneously. The ground truth trajectories were obtained by the motion capture device, a laser 3D tracker, and an RTK receiver. The dataset comprises 36 sequences (about 1 TB) captured in diverse scenarios including both indoor and outdoor environments. We evaluate state-of-the-art SLAM algorithms on M2DGR. Results show that existing solutions perform poorly in some scenarios. For the benefit of the research community, we make the dataset and tools public. The webpage of our project is <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/SJTU-ViSYS/M2DGR</uri> .

The Dataset of UAV Based High-resolution Tidal Topography at the Nakdong Estuary: Focusing on Jin-u Island and Shin-ja Island

In the tidal flats of the Nakdong Estuary, eight weirs were installed as part of the Four Major River Restoration Project in 2011, and the environment changed from a flowing stream to a still water stream. As the Nakdong River’s weir was permanently opened in February 2022, the topography and ecological environment are expected to large change. In this study, Unmanned Aerial Vehicle (UAV) photogrammetry was conducted on the tidal flats of the Nakdong Estuary in November 2021, the environment before the Nakdong River floodgates were opened. The study area was surveyed using the Network-RTK (Real-Time Kinematic) method to obtain Ground Control Point (GCP), and using an UAV, orthographic image and digital elevation model were generated for an area of 3.47 ㎢ near Jin-u island and 2.75 ㎢ near Shin-ja island. A result of spatial resolution of 1.8 cm was obtained, the result was verified using checkpoints, and results with accuracy exceeding 1 cm were obtained in both Sin-u Island and Jin-woo Island. In the future, changes in the topography and sedimentation environment of this area are expected, so it will be useful data for various research and conservation management.

Accuracy of Aerial Photoscanning with Real-Time Kinematic Technology

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Photoscanning photogrammetry is a method for obtaining and preserving three-dimensional site data from photographs. This photogrammetric method is commonly associated with small Unmanned Aircraft Systems (sUAS) and is particularly beneficial for large area site documentation. The resulting data is comprised of millions of three-dimensional data points commonly referred to as a point cloud. The accuracy and reliability of these point clouds is dependent on hardware, hardware settings, field documentation methods, software, software settings, and processing methods. Ground control points (GCPs) are commonly used in aerial photoscanning to achieve reliable results. This research examines multiple GCP types, flight patterns, software, hardware, and a ground based real-time kinematic (RTK) system. Multiple documentation and processing methods are examined and accuracies of each are compared for an understanding of how capturing methods will optimize site documentation.&lt;/div&gt;&lt;/div&gt;

Simulation research on PPP-RTK performance based on BDS GEO satellite

Precise point positioning (PPP) is one of the seven planning public services of the new generation global Beidou Navigation Satellite System (BDS), i.e. BDS-3. Up to now, the PPP service signal has already been broadcast through I channel of PPP-B2b to support decimeter level positioning within 30 min for users over China and the surrounding areas for free. Concerning the potential application of PPP real-time kinematic (PPP-RTK) in the BDS positioning service development, this paper carried out analysis and experiment of the design and evaluation of PPP-RTK through Q channel based on the existing PPP-B2b I channel signal. First, we presented the algorithm of PPP-RTK based on the undifferenced and uncombined model. Then, the format and broadcast strategy of phase delay and atmospheric delay products were discussed in detail. Finally, based on the simulation data, we analyzed the performance of PPP-RTK with different broadcast bandwidths. The results suggested that the positioning accuracy of GPS + BDS + Galileo PPP-RTK under 95% quantile were 2.3 cm and 3.3 cm in horizontal and vertical, respectively. In order to evaluate the BDS PPP-RTK service, we set the convergence thresholds as 6 cm in horizontal and 12 cm in vertical, which is given by Centimeter Level Augmentation Service of Japanese Quasi-Zenith Satellite System, and the time to converge to such thresholds were 0.5 min and 1.0 min in horizontal and vertical, respectively. Finally, the experiment considering ‘correction latency’ suggested that there was only a litter effect on the convergence speed, the positioning accuracy after convergence is roughly the same.

Integrity Monitoring of PPP-RTK Positioning; Part II: LEO Augmentation

Low Earth orbit (LEO) satellites benefit future ground-based positioning with their high number, strong signal strength and high speed. The rapid geometry change with the LEO augmentation offers acceleration of the convergence of the precision point positioning (PPP) solution. This contribution discusses the influences of the LEO augmentation on the precise point positioning—real-time kinematic (PPP-RTK) positioning and its integrity monitoring. Using 1 Hz simulated data around Beijing for global positioning system (GPS)/Galileo/Beidou navigation satellite system (BDS)-3 and the tested LEO constellation with 150 satellites on L1/L5, it was found that the convergence of the formal horizontal precision can be significantly shortened in the ambiguity-float case, especially for the single-constellation scenarios with low precision of the interpolated ionospheric delays. The LEO augmentation also improves the efficiency of the user ambiguity resolution and the formal horizontal precision with the ambiguities fixed. Using the integrity monitoring (IM) procedure introduced in the first part of this series of papers, the ambiguity-float horizontal protection levels (HPLs) are sharply reduced in various tested scenarios, with an improvement of more than 60% from 5 to 30 min after the processing start. The ambiguity-fixed HPLs can generally be improved by 10% to 60% with the LEO augmentation, depending on the global navigation satellite system (GNSS) constellations used and the precision of the ionospheric interpolation.

Realization and evaluation of real-time uncombined GPS/Galileo/BDS PPP-RTK in the offshore area of China’s Bohai sea

The real-time kinematic (RTK) technology has been widely used as the high-precision positioning method in the offshore area. However, RTK requires a bi-directional communication and groups measurement errors together, thereby limiting its mass-market applications. Combining the advantages of precise point positioning (PPP) and RTK, PPP-RTK has become one of the hotspot technologies in the mass market. In this contribution, we propose the uncombined multi-GNSS PPP-RTK model using uncalibrated phase delays (UPDs) estimated from the legacy ionosphere-free and Melbourne-Wübbena combination. With the UPDs estimated based on 14 regional stations, we conduct PPP ambiguity resolution (AR) at 3 augmentation stations and derive precise atmospheric corrections, i.e., RMS of zenith tropospheric and slant ionospheric correction can be up to 4.89 mm and 2.20 cm, respectively. After applying atmospheric correction, the correct fixed solution of four on-board kinematic experiments can be better than 95% and the positioning accuracy can be better than 5 cm in both horizontal and vertical direction, showing the encouraging performance similar to RTK in the offshore area.

Deriving First Floor Elevations within Residential Communities Located in Galveston Using UAS Based Data

Flood damages occur when just one inch of water enters a residential household and models of flood damage estimation are sensitive to first-floor elevation (FFE). The current sources for FFEs consist of costly survey-based elevation certificates (ECs) or assumptions based on year built, foundation type, and flood zone. We sought to address these limitations by establishing the role of an Unmanned Aerial System (UAS) to efficiently derive accurate FFEs. Four residential communities within Galveston Island, Texas were selected to assess efficient flight parameters required for UAS photogrammetry within the built environment. A real-time kinematic positioning enabled (RTK) UAS was then used to gather georeferenced aerial imagery and create detailed 3D photogrammetric models with ±0.02 m horizontal and ±0.05 m vertical accuracies. From these residential models, FFEs and other structural measurements present in traditional ECs were obtained. Comparative statistical analyses were performed using the UAS-based measurements and traditional EC measurements. UAS based FFE measurements achieved 0.16 m mean absolute error (MAE) across all comparative observations and were not statistically different from traditional EC measures. We conclude the RTK enabled UAS approach is an efficient, cost-effective method in establishing accurate FFEs and other flood-sensitive measures in residential communities.

Assessment of the performance of GPS/Galileo PPP-RTK convergence using ionospheric corrections from networks with different scales

The rapid convergence of precise point positioning real-time kinematics (PPP-RTK) with centimeter-level accuracy is of utmost importance for many applications. One way of accelerating this convergence is to explore the use of ionospheric models and multiple global navigation satellite system (GNSS) observations, e.g., Global Positioning System (GPS) and Galileo Satellite Navigation System (Galileo) observations. Because the temporal and spatial variations of the ionosphere are significant, convergence analysis of PPP-RTK should be investigated in networks with different scales, especially networks with large differences in their scales. This study describes the convergence performance of PPP-RTK using GPS/Galileo observations derived from networks with different scales under medium ionospheric conditions. Slant ionospheric corrections were first estimated from the reference network and then imported as virtual observations to enhance the convergence performance of PPP-RTK at the user interface. The results show that for the 165-km reference site spacing, the portions of single-differenced (SD) ionospheric residuals within 0.3 total electron content units (TECU) were 85.2% and 81.7% for the GPS and Galileo observations, respectively. Considering the 90th percentile of horizontal position errors, the PPP-RTK convergence time within the network with 165-km spacing was shortened from 2.5 min for GPS-only observations to 2.0 min for integrated GPS + Galileo observations. For the network of about 50 km, the proportions of the SD ionospheric residuals of the GPS and Galileo constellation within 0.3 TECU were 95.9% and 82.8%, respectively. The PPP-RTK convergence time of the 90th percentile horizontal positioning errors based on GPS-only observations was 2.0 min but 1.5 min based on integrated GPS + Galileo observations. Using GPS and Galileo observations, the convergence time could be reduced by 25% for the network with 50-km spacing. Our results suggest that the convergence time of PPP-RTK depends on the scale of the reference network and becomes shorter as the scale of the network decreases. Compared with the GPS-only PPP-RTK, the GPS/Galileo PPP-RTK could shorten the convergence time further.Graphical

Brain Response to a Knee Proprioception Task Among Persons With Anterior Cruciate Ligament Reconstruction and Controls.

Knee proprioception deficits and neuroplasticity have been indicated following injury to the anterior cruciate ligament (ACL). Evidence is, however, scarce regarding brain response to knee proprioception tasks and the impact of ACL injury. This study aimed to identify brain regions associated with the proprioceptive sense of joint position at the knee and whether the related brain response of individuals with ACL reconstruction differed from that of asymptomatic controls. Twenty-one persons with unilateral ACL reconstruction (mean 23 months post-surgery) of either the right (n = 10) or left (n = 11) knee, as well as 19 controls (CTRL) matched for sex, age, height, weight and current activity level, performed a knee joint position sense (JPS) test during simultaneous functional magnetic resonance imaging (fMRI). Integrated motion capture provided real-time knee kinematics to activate test instructions, as well as accurate knee angles for JPS outcomes. Recruited brain regions during knee angle reproduction included somatosensory cortices, prefrontal cortex and insula. Neither brain response nor JPS errors differed between groups, but across groups significant correlations revealed that greater errors were associated with greater ipsilateral response in the anterior cingulate (r = 0.476, P = 0.009), supramarginal gyrus (r = 0.395, P = 0.034) and insula (r = 0.474, P = 0.008). This is the first study to capture brain response using fMRI in relation to quantifiable knee JPS. Activated brain regions have previously been associated with sensorimotor processes, body schema and interoception. Our innovative paradigm can help to guide future research investigating brain response to lower limb proprioception.

Modeling and assessment of atmospheric delay for GPS/Galileo/BDS PPP-RTK in regional-scale

Combining advantages of precise point positioning (PPP) and real-time kinematic (RTK), PPP-RTK has become a promising technology in the mass-market positioning. When performing PPP-RTK, atmospheric corrections enable the user fast ambiguity resolution as well as centimeter accuracy. However, the legacy method of obtaining atmospheric corrections, i.e., interpolating the atmospheric delay based on nearby reference stations, is not regular in space and needs the reference station coordinate information, thereby limiting real-time professional applications. In this contribution, a low-degree polynomial with regular grid residuals is investigated. Forming between-satellite single-differenced slant ionospheric delay, we theoretically analyze the reference network size. Afterwards, the zenith tropospheric delay and slant ionospheric delay accuracy using zero-, first- and second-degree polynomials in calm atmospheric periods are about (5.6, 4.7 and 4.7) mm and (1.9, 1.3 and 1.3) cm. It is therefore recommended to adopt the first-degree polynomial model in terms of the accuracy and transmission load.

On the 3D Reconstruction of Coastal Structures by Unmanned Aerial Systems with Onboard Global Navigation Satellite System and Real-Time Kinematics and Terrestrial Laser Scanning

A wide variety of hard structures protect coastal activities and communities from the action of tides and waves worldwide. It is fundamental to monitor the integrity of coastal structures, as interventions and repairs may be needed in case of damages. This work compares the effectiveness of an Unmanned Aerial System (UAS) and a Terrestrial Laser Scanner (TLS) to reproduce the 3D geometry of a rocky groin. The Structure-from-Motion (SfM) photogrammetry technique applied on drone images generated a 3D point cloud and a Digital Surface Model (DSM) without data gaps. Even though the TLS returned a 3D point cloud four times denser than the drone one, the TLS returned a DSM which was not representing about 16% of the groin (data gaps). This was due to the occlusions encountered by the low-lying scans determined by the displaced rocks composing the groin. Given also that the survey by UAS was about eight time faster than the TLS, the SFM-MV applied on UAS images was the most suitable technique to reconstruct the rocky groin. The UAS remote sensing technique can be considered a valid alternative to monitor all types of coastal structures, to improve the inspection of likely damages, and to support coastal structure management.

Under the Sand: Navigation and Localization of a Micro Aerial Vehicle for Landmine Detection with Ground-Penetrating Synthetic Aperture Radar

Ground-penetrating radar mounted on a micro aerial vehicle (MAV) is a promising tool to assist humanitarian landmine clearance. However, the quality of synthetic aperture radar images depends on accurate and precise motion estimation of the radar antennas as well as generating informative viewpoints with the MAV. This paper presents a complete and automatic airborne ground-penetrating synthetic aperture radar (GPSAR) system. The system consists of a spatially calibrated and temporally synchronized industrial grade sensor suite that enables navigation above ground level, radar imaging, and optical imaging. A custom mission planning framework allows generation and automatic execution of stripmap and circular GPSAR trajectories controlled above ground level as well as aerial imaging survey flights. A factor graph based state estimator fuses measurements from dual receiver real-time kinematic (RTK) global navigation satellite system (GNSS) and an inertial measurement unit (IMU) to obtain precise, high-rate platform positions and orientations. Ground truth experiments showed sensor timing as accurate as 0.8 µs and as precise as 0.1 µs with localization rates of 1 kHz. The dual position factor formulation improves online localization accuracy up to 40 % and batch localization accuracy up to 59 % compared to a single position factor with uncertain heading initialization. Our field trials validated a localization accuracy and precision that enables coherent radar measurement addition and detection of radar targets buried in sand. This validates the potential as an aerial landmine detection system.