Height Error Research Articles

A Fizeau interferometry stitching system to characterize X-ray mirrors with sub-nanometre errors

We present the development of a Fizeau interferometer stitching system to characterize the surface profile of state-of-the-art X-ray optics for synchrotron and free electron laser sources. Controls and acquisition software precisely translate and rotate the surface under test in synchrony with data capture by a Zygo Verifire HDX interferometer. Overlapping sub-aperture images are combined into a composite, high-spatial resolution topographical image of the entire optical surface using PyLOSt stitching software produced by the MooNpics collaboration. After minimization of random and systematic measurement errors, system performance was quantified by characterizing two challenging optics. These optics represent extreme cases for synchrotron X-ray mirrors: an aspheric elliptical profile with a slope error of ∼50 nrad rms, and a corresponding height error of 0.2 nm rms; and a chirped periodic structure superimposed upon a strong curvature (radius ∼ 9.33 m). Results are in very good agreement with the Diamond-NOM slope profilometer and Bruker GTX stitching micro-interferometer. Without a specialist transmission reference, both optics could not be measured by the interferometer without pitch and translation stitching. Any individual HDX scan, relative to the average of the ensemble, has an average slope error repeatability of < 15 nrad rms. After calibration of the transmission reference flat and zoom factor, a reproducibility of ∼ 27 nrad rms compared to the Diamond-NOM, was achieved for the elliptically curved mirror.

Novel cooperative localization method of over-the-horizon shortwave emitters based on direction-of-arrival and time-difference-of-arrival measurements

The location of long-distance shortwave radiation sources is practically significant in national defense security. Shortwave multistation-positioning systems mainly include direction-of-arrival (DOA) and time-difference-of-arrival (TDOA) intersection locations. These two systems have their advantages and disadvantages in terms of performance. To combine the advantages of these two positioning technologies, this study focuses on the cooperative positioning problem based on DOA and TDOA measurements. First, the two-dimensional DOA and TDOA observation models are established for the over-the-horizon propagation scenario. Subsequently, the Cramér-Rao lower bound (CRLB) of positioning accuracy is derived in the presence of measurement errors in virtual ionosphere height. Aiming at the strong nonlinear characteristics of the observation equations, a new DOA/TDOA cooperative localization method is proposed. Finally, the asymptotic efficiency of the new estimator is proved using the first-order error analysis theory. The new method comprises two stages. In the first stage, the shortwave DOA observation equation is transformed into a pseudo-linear observation equation by introducing an auxiliary variable, as well as solving a quadratic equation with one unknown. Next, an optimization model with two quadratic equality constraints is constructed, and an iterative optimization algorithm based on matrix $~\bf{QR}$ decomposition is proposed to obtain an intermediate estimate of the emitter position. The second stage transforms the shortwave TDOA observation equation into a pseudo-linear observation equation by combining the intermediate estimates given in the first phase. Also, an iterative-constrained weighted-least-squares estimator based on the matrix decomposition is proposed again to localize the emitter. Simulation results show that the new cooperative localization method has good global convergence, the localization performance can reach the CRLB, and the obtained cooperative gain is quite high.

Assessment of Geo-Kompsat-2A Atmospheric Motion Vector Data and Its Assimilation Impact in the GEOS Atmospheric Data Assimilation System

Korea’s second geostationary meteorological satellite, Geo-Kompsat-2A (Geostationary-Korean Multi-Purpose Satellite-2A, GK2A), was successfully launched on 4 December 2018. GK2A generates Atmospheric Motion Vectors (AMVs) every 10 min in the full disk area. This data has been disseminated via Global Telecommunication System (GTS) since 25 October 2019. This article evaluates the quality of GK2A AMVs in the Goddard Earth Observing System (GEOS) atmospheric data assimilation system (ADAS). The data show slow wind speed biases at 200–300 hPa and 600–800 hPa in the northern and southern hemispheres. These biases are caused by observation height assignment errors near jet streams. The Equivalent Blackbody Temperature (EBBT) method of GK2A tends to assign clouds at higher altitude, which mainly causes slow wind speed biases, especially in the lower atmosphere. The IR/WV intercept method of GK2A assigns clouds slightly lower in the atmospheric layers below the altitude of 400 hPa, which causes positive biases. Quality control (QC) criteria to select the most suitable GK2A AMV data for assimilation are presented based on these quality assessments. A new QC criterion utilizing height errors within the GEOS ADAS is introduced to exclude data with slow wind speed biases and large errors. GEOS forecast accuracy is slightly improved after assimilating GK2A AMVs along with other conventional, radiance, and satellite winds which include AMVs made by the Himawari-8 satellite in nearly the same observational area of GK2A. Additionally, the present work shows that GEOS forecasts can be significantly improved, especially in the tropics and southern hemisphere after assimilating GK2A data in the absence of Himawari-8 AMVs. This study demonstrates that GK2A AMV data is a valuable data source to enhance the robustness of GEOS ADAS.

Pseudo Wigner-Ville distribution for 3D white light scanning interferometric measurement.

White light scanning interferometry is a commonly used optical measurement method for three-dimensional (3D) surface profiles. In the case of large phase errors, accurate height values can generally be obtained indirectly from the interferometric signal envelope information derived using various envelope extraction methods. However, the current envelope extraction algorithms have the disadvantages of low robustness, increasing the half-width of the envelope information, and requiring correct parameter settings in advance. In this study, the pseudo Wigner-Ville distribution is modified and applied to white light scanning interferometric 3D measurement to avoid the above-mentioned drawbacks. Simulations and experiments are performed in a single-frequency mode (only the approximate central wave-number is used to guide both the proposed and wavelet transform methods). The simulation results prove that the proposed method has a 31.7% higher reconstruction accuracy than the wavelet transform method under a 25 dB signal to noise ratio condition. Concurrently, the proposed method is insensitive to the change in the central wavelength with a constant central wave-number parameter and has a good extraction effect for a long coherent length. The experiments measure standard step objects (VLSI standard, 1.761 ± 0.01 µm), and the reconstruction height error of the proposed method is 0.0035 µm. Simulations and experiments show that the proposed method can adaptively provide accurate envelope information after half-width reduction under the condition that only the approximate central wave-number a priori knowledge is used. Simultaneously, the proposed method is shown to be robust and effective.

Online workpiece height estimation method based on discharge location detection for reciprocated traveling WEDM

This paper proposes a novel online workpiece height estimation system for reciprocated traveling wire-EDM by utilizing a discharge location detection (DLD) associated with a pulse discharge state detector. Based on the distribution of detected discharge locations, the workpiece height can be estimated. Furthermore, by utilizing the Richardson–Lucy super-resolution algorithm, the estimation error of workpiece height is reduced by 65%, from 3.30 mm to 1.15 mm for workpieces with a height of 10∼35 mm. During the verification experiments of cutting a stepwise workpiece and a hollow workpiece both with sharp height variations, the workpiece heights are estimated precisely and the machining efficiencies are improved by 27.9% and 74.5% respectively by adjusting the discharge gap servo control parameter according to the workpiece height estimation results. Since the DLD method proposed in this paper has not been found to be significantly affected by process parameters, the workpiece height estimation method and the corresponding adaptive control approach are feasible for industrial applications.

Evaluation of a Linear Inversion Method for retrieval of directional wave spectra from SAR look cross spectra

The feasibility of a Linear Inversion Method applied to Synthetic Aperture Radar cross spectra to retrieve wave directional spectra is investigated. The proposed method is computationally efficient and does not require any a priori information from wave or atmospheric models, as is usually the case with other approaches. It is also comparatively less sensitive to low signal-to-noise ratio image spectra, which in general hinders the disambiguation of the retrieved directional wave spectrum. Several test cases were computed employing a simulator of complex SAR image spectra considering a broad range of values of steepness for the Envisat and Sentinel-1 satellite configurations. The results of the simulated cases were employed as lookup tables to correct biases while retrieving directional wave spectra from Level 1 cross spectra. As the nonlinearities, not accounted for when applying a linear inversion, are dependent on satellite configuration and on the relative position of the peak wave spectrum in relation to the azimuth cut-off, it is possible to quantify them through numerical simulations. The SAR wave spectra retrieved with the Linear Inversion Method from an Envisat ground track were evaluated against the ECMWF reanalysis ERA5 and compared to the results of ESA Level 2 WVW wave mode spectra. The SAR-inverted wave spectra, retrieved with both methods, presented similar results in terms of root-mean-square error (RMSE) and scatter index (SI) for significant wave height, peak wavelength and peak propagation direction. Specifically for significant wave height, the Linear Inversion Method yielded a bias of −0.14 m, a SI of 0.34 and a RMSE of 0.44 m for a segment of ground track over the Pacific Ocean employed in our validations. The directional wave spectra retrieved with the Linear Inversion Method presented better similarity with the ERA5 spectra, in comparison with the WVW spectra. Moreover, in around one third of the cases, the ESA method did not resolve the directional ambiguity. The preliminary results employing the Linear Inversion Method are encouraging, specially considering its simplicity and performance against the ESA distributed wave spectra.

A New Strategy for Forest Height Estimation Using Airborne X-Band PolInSAR Data

Because the penetration depth of electromagnetic waves in forests is large in the longer wavelength band, most traditional forest height estimation methods are carried out using polarimetric interferometry synthetic aperture radar (PolInSAR) data of the L or P band, and the estimation method is a three-stage method based on the random volume over ground (RVoG) model. For X-band electromagnetic waves, the penetration depth of radar waves in forests is limited, so the traditional forest height estimation method is no longer applicable. In view of the above problems, in this paper we propose a new forest height estimation strategy for airborne X-band PolInSAR data. Firstly, the sub-view interferometric SAR pairs obtained via frequency segmentation (FS) in the Doppler domain are used to extend the polarimetric interferometry coherence coefficient (PolInCC) range of the original SAR image under different polarization states, so as to obtain the accurate ground phase. For the determination of the effective volume coherence coefficient (VCC), part of the fitting line of the extended-range PolInCC distribution that is intercepted by the fixed extinction coherence coefficient curve (FECCC) of the fixed range is averaged to obtain the accurate effective VCC. Finally, the high-precision forest canopy height in the X-band is estimated using the effective VCC with the ground phase removed in the look-up table (LUT). The effectiveness of the proposed method was verified using airborne-measured data obtained in Shaanxi Province, China. The comparison was carried out using different strategies, in which we substituted one step of the process with the conventional method. The results indicated that our new strategy could reduce the root mean square error (RMSE) of the predicted canopy height vastly to 1.02 m, with a lower estimation height error of 12.86%.

Alveolar bone measurements in magnetic resonance imaging compared with cone beam computed tomography: a pilot, ex-vivo study

Objectives To compare alveolar bone height and width measurements from zero-echo-time MRI (ZTE-MRI) and cone beam CT (CBCT), in human specimens. Material and methods Twenty posterior edentulous sites in human cadaver specimens were imaged with CBCT and ZTE-MRI. Bone height and width at 1, 3, 5, 7 and 9 mm from the top of the alveolar ridge was measured by two trained observers in cross-sections of a site where an implant was to be planned. Twenty percent of the sample was measured in duplicate to assess method error and intra-observer reproducibility (ICC). The differences between CBCT and ZTE-MRI measurements were compared (t-test). Results Inter- and intra-observer reproducibility was >0.90. The method error (average between observers) for bone height was 0.45 mm and 0.39 mm, and for bone width (average) was 0.52 mm and 0.80 mm (CBCT and ZTE-MRI, respectively). The majority of the bone measurement differences were statistically insignificant, except bone width measurements at 5 mm (p ≤ .05 for both observers). Mean measurement differences were not larger than the method error. Conclusion ZTE-MRI is not significantly different from CBCT when comparing measurements of alveolar bone height and width.

Implantable collamer lens sizing based on measurement of the sulcus-to-sulcus distance in ultrasound biomicroscopy video clips and ZZ ICL formula

BackgroundTo evaluate a new method of implantable collamer lens (ICL) sizing based on ultrasound biomicroscopy (UBM) video clips.MethodsThis observational study included consecutive patients with myopia and myopic astigmatism scheduled for V4c toric ICL (TICL) implantation (STAAR) at Hangzhou MSK Eye Hospital (October 2020 to November 2020). Sulcus-to-sulcus (STS) distance, lens thickness (LT), and clinical refraction were measured preoperatively. The ZZ ICL formula (provides the predicted vault height and refraction based on TICL size, intraocular meridian, power, and eye parameters, including STS distance and LT) was used to select TICL size and predict vault height and residual refraction, which was also compared with the STAAR software recommended. Vault and residual refraction were measured at 3 months postoperatively.ResultsThe analysis included 168 eyes in 84 patients. Postoperative vault size was comparable to that predicted by the ZZ ICL formula (528 ± 193 vs. 545 ± 156 μm, P = 0.227). Vault prediction error (PE) by the ZZ ICL formula was within 100, 300, and 500 μm in 40.48%, 88.10%, and 100% of eyes, respectively. Spherical equivalent (SE) and absolute cylindrical refractive error were 0.36 ± 0.48 and 0.40 ± 0.31 D at 3 months postoperatively. The SE PE, absolute cylindrical PE, and percentages of eyes with an absolute cylindrical PE within ± 0.50 D and ± 1.00 D were lower for the ZZ ICL formula than for the STAAR software (P < 0.01).ConclusionsCombining measurements obtained in UBM video clips with the ZZ ICL formula provides an effective method of sizing TICLs and predicting vault height and residual refractive error.

3D Evaluation of fine-scale normalised DSMs in urban settings

Humankind often needs to accurately model, identify and spatially quantify aboveground phenomena on the Earth’s surface for informed decision-making. Height data derived from digital elevation models (DEMs) is often used to achieve this. This study conducted a deterministic assessment of three normalised digital surface models (nDSMs) of different spatial resolutions, namely 2m, 4m and 12m, derived from VHR digital stereo aerial photography, tri-stereo Pléiades imagery and Tandem-X InSAR data, respectively. Covering a predominantly built-up area within a city landscape, the nDSMs were vertically and volumetrically compared to assess their quality and fit-for-use. In each case a consistent systematic evaluation was accomplished against a lidar derived reference surface at matching spatial resolutions (co-registered) using a semi-automated GIS routine. The relative height and volumetric errors were statistically analysed and described, including those computed individually over nine urban land cover/land use (LCLU) classes and several selected large buildings. Higher vertical accuracies were reported across single storey structures and areas with no to little or short vegetation, as apposed to substantially lower accuracies obtained over multi-levelled buildings and tall (dense) woody vegetation. Here significant underestimations of volumes exacerbated by lower spatial resolutions were also observed across each nDSM. Conversely, notable volume overestimations were found over predominantly grass-covered areas in especially the finer-scaled nDSMs. VHR elevation data is recommended to model and quantify aboveground elements spatially in 3D (e.g. buildings, earthworks and woody vegetation) in urban landscapes, but a sensitivity test beforehand remains critical to ensure more reliable outcomes for users and stakeholders alike.

Prediction of deposition bead geometry in wire arc additive manufacturing using machine learning

The deposition bead geometry in the arc strike zone is often abnormal compared with that in the middle deposition zone. The accumulation of these errors in the deposition process results in defects in the overall geometry of the deposition bead. To prevent the accumulation of such errors, this study aimed to address the irregular deposition bead shape and deviation of the deposition bead geometry in the arc strike zone without changing the deposition path or introducing external devices. A support vector machine classifier, which is a typical application of machine-learning classification models, was used to obtain the deposition condition ranges for a uniform deposition bead shape. The deposition conditions of the arc strike and middle deposition zones that could reduce the deviation of the deposition bead geometry in the arc strike zone were obtained using support vector machine regression. These conditions were applied in the form of variable conditions in single-path deposition. Five-layer deposition was conducted to validate the regression model. As a result of the validation experiment, the average height and width errors in the arc strike zone were 0.36% and 1.28%, respectively, and the average height and width errors in the middle deposition zone were 0.64% and 1.26%, respectively. Therefore, the regression model can be used for accurate deposition, thereby reducing the post-processing cost.

Congruence through repeatability of position solutions by different GNSS survey techniques

In this study, we determined three-dimensional (3D) position coordinates for eight new Continuous Operating Reference Stations (CORS) in Ghana through three different GNSS positioning techniques. The three GNSS positioning techniques whereby the network of CORS was tied to ITRF14 and War Office 1926 datums included:1) Precise Point Positioning (PPP); 2) Precise Differential GNSS (PDGNSS), using reference stations based on ITRF14; and 3) PDGNSS, using reference stations based on War Office. The PPP solutions were computed using the Canadian Spatial Reference System Precise Point Positioning software (CSRS-PPP), available online and as an open source GNSS laboratory tool software (gLAB). The PDGNSS solutions were obtained from OPUS and AUSPOS online services, as well as from self-post-processing using Topcon Tools software v8.2.3. All solutions were computed using 24-hour data for twelve consecutive days in the month of October 2018 (GPS DoY 284 to GPS DoY 295). The quality, reliability, and acceptability of position solutions were measured by computing the average positioning error, the rate of ambiguity resolution and the repeatability ratios of the solutions. The variability of coordinate differences for each pair of different positioning techniques was computed to determine their solution congruences. Ultimately, , the average positioning errors in northing, easting, and height were 0.003m, 0.005m and 0.009m, respectively. The rate of ambiguity resolution was between 75.3% and 90.3%. Repeatability ratios ranged between 1: 68,500,000 and 1: 411,100,000. Finally, the minimum and maximum range of variability in coordinate differences for each pair of positioning techniques was 1mm to 16mm for horizontal positions and 2mm to 137mm for vertical positions.

Estimating Carbon Stocks and Biomass Expansion Factors of Urban Greening Trees Using Terrestrial Laser Scanning

Urban forest carbon sequestration represents an important component of the global forest carbon pool; however, accurate measurements are limited by the inability of existing field stand models to match the specificity of urban greening species. Herein, canopy volume, carbon stock, and the biomass expansion factor (BEF) of 30 Koelreuteria paniculate trees were measured based on terrestrial laser scanning (TLS) and compared to the results of existing wood volume and carbon stock model measurements. The findings revealed that (1) TLS point cloud data were highly reproducible and accurate (root mean square error of tree height and diameter at breast height were ±0.35 m and ±0.33 cm, respectively). (2) Owing to human interference and cluttered urban environments, the BEF of urban greening tree species fluctuated irregularly, considerably different from that of natural forest stands. (3) Leaf carbon stocks were influenced by the size of the voxel. (4) Different tree measurement factors maintained variable degrees of influence on BEF (height under branch, volume of thick branch, crown width, and projected areas of tree-crown produced correlation coefficients of −0.64, 0.54, 0.45, and 0.43, respectively). Accordingly, the carbon stock and BEF of urban greening tree species can be accurately calculated via TLS without damage.

The ATL08 as a height reference for the global digital elevation models

ABSTRACT High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications. The Ice, Cloud, and Land elevation Satellite 2 (ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights, but it has not been fully evaluated. Hence, this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and TanDEM-X (TDX) DEMs over vegetated mountainous areas. We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy. Then, the results were evaluated against a reference airborne LiDAR digital terrain model (DTM), by selecting 10,000 points over the entire area and comparing the accuracy of ASTER, SRTM, and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER, SRTM, and TDX DEMs assessed by the ATL08 strong beams, weak beams, and all beams. We also detected the impact of the terrain aspect, slope, and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty. Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%; while the weak beams accuracy was enhanced by 74.05%. Furthermore, slope strongly influenced ATL08 height errors and height uncertainty; especially on the weak beams. The errors induced by the slope significantly decreased when the uncertainty levels were reduced to <20 m. The evaluations of ASTER, SRTM, and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams. These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions.

A Deep Learning-Based Method for Extracting Standing Wood Feature Parameters from Terrestrial Laser Scanning Point Clouds of Artificially Planted Forest

The use of 3D point cloud-based technology for quantifying standing wood and stand parameters can play a key role in forestry ecological benefit assessment and standing tree cultivation and utilization. With the advance of 3D information acquisition techniques, such as light detection and ranging (LiDAR) scanning, the stand information of trees in large areas and complex terrain can be obtained more efficiently. However, due to the diversity of the forest floor, the morphological diversity of the trees, and the fact that forestry is often planted as large-scale plantations, efficiently segmenting the point cloud of artificially planted forests and extracting standing wood feature parameters remains a considerable challenge. An effective method based on energy segmentation and PointCNN is proposed in this work to address this issue. The network is enhanced for learning point cloud features by geometric feature balance model (GFBM), enabling the efficient segmentation of tree point clouds from forestry point cloud data collected by terrestrial laser scanning (TLS) in outdoor environments. The 3D Forest software is then used to obtain single wood point cloud after semantic segmentation, and the extracted single wood point cloud is finally employed to extract standing wood feature parameters using TreeQSM. The point cloud semantic segmentation method is the most important part of our research. According to our findings, this method can segment datasets of two different artificially planted woodland point clouds with an overall accuracy of 0.95 and a tree segmentation accuracy of 0.93. When compared with the manual measurements, the root-mean-square error (RMSE) for tree height in the two datasets are 0.30272 and 0.21015 m, and the RMSEs for the diameter at breast height are 0.01436 and 0.01222 m, respectively. Our method is a robust framework based on deep learning that is applicable to forestry for extracting the feature parameters of artificially planted trees. It solves the problem of segmenting tree point clouds in artificially planted trees and provides a reliable data processing method for tree information extraction, trunk shape analysis, etc.

More Detailed Disturbance Measurement and Active Disturbance Rejection Altitude Control for a Flapping Wing Robot Under Internal and External Disturbances

With the goal of designing a biologically inspired robot that can hold a stable hover under internal and external disturbances. We designed a tailless Flapping-wing Micro Aerial Vehicle (FMAV) with onboard 3D velocity perception. In this way, the wind disturbance caused by the relative motion of the FMAV can be quantified in real time based on the established altitudinal dynamics model. For the rest of the total disturbance, an active disturbance rejection controller is proposed to estimate and suppress those disturbances. In comparison with the traditional PID controller, this proposed approach has been validated. The results show that, in the hovering flight with the internal unmodeled dynamics, the root-mean-square of height controlled is only 2.53 cm. Even with the different weights of loads mounting on the FMAV, the ascending trajectory of flights remains impressively consistent. In the forward flight with the external disturbance, the root-mean-square error of height controlled is 2.78 cm. When the FMAV flies over a ladder introducing an abrupt external disturbance, the maximum overshoot is only half of that controlled by the PID controller. To our best knowledge, this is the first demonstration of FMAVs with the capability of sensing motion-generated wind disturbance onboard and handling the internal and external disturbances in hover flight.

A Joint Method for Wave and Wind Field Parameter Inversion Combining SAR with Wave Spectrometer Data

Synthetic aperture radar (SAR) and wave spectrometer are common methods for observing the ocean wind field and waves on the sea surface, but both have limitations. Due to the influence of velocity bunching modulation, SAR wave observation is limited by the azimuth cut-off phenomenon. Meanwhile, SAR relies on an external wind direction source, so it is difficult for SAR to observe wind fields independently. There is no azimuthal cut-off phenomenon when the spectrometer observes the sea surface, but its azimuth resolution is much lower than SAR. Combining the above characteristics, the joint inversion of SAR and wave spectrometer for sea-state parameters becomes possible. In this paper, a joint method for wind field and wave parameter inversion combining SAR with spectrometer data is proposed. In this method for wave parameter inversion, the wave spectrum of the spectrometer was used as a first-guess spectrum of SAR wave spectrum inversion, the fit wave spectrum obtained by joint inversion and the modified wave spectrum of the spectrometer were fused to form a new spectrum, and the wave parameters were calculated. For wind field parameter inversion, wind direction was obtained using a wave spectrometer, and was used as the input of the SAR wind field inversion. Wind speed was obtained using the CMOD5.N method. Collocated data from Sentinel-1 SAR, the wave spectrometer, the National Data Buoy Center (NDBC) buoy, and the European Centre for Medium-Range Weather Forecasting (ECMWF) are used to verify the proposed method. Sea parameters retrieved from the spectrometer and SAR are compared to the buoy and ECMWF data. The results show that the root mean square errors of significant wave height, mean wave period, wind direction and wind speed are 0.37 m, 1.02 s, 22.7° and 1.06 m/s with ECMWF data, and 0.35 m, 0.78 s, 18.22° and 0.92 m/s with buoy data, respectively. By comparing the inversion results with the L2 products of SAR and SWIM, it can be concluded that the inversion accuracy of the joint method is higher in the middle and low sea conditions. Therefore, the joint inversion method for wind field and wave parameters proposed in this paper has good results, which verifies the accuracy of the joint inversion method.

An efficiency and quality based automatic drilling-riveting system for aero-structures assembly

Considering the constantly increasing demand for aircraft products, the development of automatic drilling-riveting machine tool systems is discussed in this paper. A structural conceptual design method considering both efficiency and quality is proposed. Particularly, a drilling-riveting machine tool system including single-column machine tool, light-weight end-effector, and assisting fixture system is built. The positioning error coordinates variation model is analyzed, and the ranges of reasonable processing parameters are determined. An experiment is conducted on the developed system to show satisfactory drilling-riveting quality and efficiency: compared with the position error of other similar systems, the position error with 0.082 mm is reduced by 41.42%, and the accuracy of aperture reaches H8, the rivets head height error ≤0.8 mm, and drilling and riveting efficiency can reach 6/min and 8/min.

Research on a Measurement Method for the Ocean Wave Field Based on Stereo Vision

The wave parameter is an important environmental input condition. Traditional contact wave measurement methods are unable to meet the requirements of high precision, non-contact, and ship wave field assessment. Alternatively, stereo vision technology can realize a non-contact and mobile form of measurement. However, this technology suffers from poor timeliness and adaptability. This paper proposes a comprehensive wave measurement method that is based on stereo vision, wherein the gridding of siftGPU is used to achieve the fast matching of large images. The whole algorithm can be run within 6 s and it guarantees more than 20,000 feature-matching logarithms. Furthermore, by utilizing the least squares method and sea surface wave surface theory, the sea surface base level can be calculated without control points, along with the inversion of the sea wave parameters (wave height, period, and wave direction) and error point fitting. The rationality and superiority of the algorithm were verified through multiple comparison experiments. Compared with the Richard Brancker Research (RBR) wave height meter, the measurement error of the wave height is less than 10%, the period error is less than 0.5 s, and the wave direction error is less than 10° with the proposed method.

Assessment of underlying topography and forest height inversion based on TomoSAR methods

ABSTRACT Due to the strong penetrability, long-wavelength synthetic aperture radar (SAR) can provide an opportunity to reconstruct the three-dimensional structure of the penetrable media. SAR tomography (TomoSAR) technology can resynthesize aperture perpendicular to the slant-range direction and then obtain the tomographic profile consisting of power distribution of different heights, providing a powerful technical tool for reconstructing the three-dimensional structure of the penetrable ground objects. As an emerging technology, it is different from the traditional interferometric SAR (InSAR) technology and has advantages in reconstructing the three-dimensional structure of the illuminated media. Over the past two decades, many TomoSAR methods have been proposed to improve the vertical resolution, aiming to distinguish the locations of different scatters in the unit pixel. In order to cope with the forest mission of European Space Agency (ESA) that is designed to provide P-band SAR measurements to determine the amount of biomass and carbon stored in forests, it is necessary to systematically evaluate the performance of forest height and underlying topography inversion using TomoSAR technology. In this paper, we adopt three typical algorithms, namely, Capon, Multiple Signal Classification (MUSIC), and Compressed Sensing (CS), to evaluate the performance in forest height and underlying topography inversion. The P-band airborne full-polarization (FP) SAR data of Lopè National Park in the AfriSAR campaign implemented by ESA in 2016 is adopted to verify the experiment. Furthermore, we explore the effects of different baseline designs and filter methods on the reconstruction of the tomographic profile. The results show that a better tomographic profile can be obtained by using Hamming window filter and Capon algorithm in uniform baseline distribution and a certain number of acquisitions. Compared with LiDAR results, the root-mean-square error (RMSE) of forest height and underlying topography obtained by Capon algorithm is 2.17 m and 1.58 m, which performs the best among the three algorithms.