Height Error Research Articles

A Novel Motion Compensation Method Based on Height Term Removing for Spotlight SAR on Circular Trajectories

For spotlight synthetic aperture radar (SAR) on circular trajectories, the phase error caused by motion error is 2-D space-variant. For the conventional motion compensation (MOCO) algorithm, the imaging scene is generally segmented into many sub-regions to compensate for the space-variant phase error. However, the complex phase error results in that fact that it is difficult to obtain the quantitative criterion of scene segmentation. To address this issue, we propose a novel MOCO algorithm. This method contains three steps; the first step is non-space-variant phase error compensation; the second step is to remove the height term; the third step is space-variant phase error compensation. Among these steps, the most critical operation is removing the height term. In the distance equation, the height term is independent of the ground target coordinate. Hence, it can be removed by a serial of operations containing resampling and phase compensation. Through removing height term, it doesn’t only compensate the height error but also makes the residual phase error into 1-D space-variant. Then, the phase error is exclusively related to the radius error and the target abscissa. Hence, after compensating for the space-variant error, it only needs to segment scene along the abscissa direction. Meanwhile, it can gain the quantitative criterion of scene segmentation to guarantee the phase error variation range is less than $\pi /{4}$ in each sub-scene. Eventually, some simulations are conducted to illustrate that the proposed method is valid.

A Rapid Plotting Algorithm of Geodetic Line within Arch Height Error Threshold Limits under Mercator Projection

In view of the problem that the interpolated distance parameters and the plotting precision of the geodetic line cannot be quantitatively regulated and adaptively matched, this paper extends the application of the solution method for constant line segment by considering the angle of the constant line and the geodetic line to the quantitative evaluation and control process of the error of the geodetic line plotting. Using the strategy of limiting the overall length error of the geodetic line plotting by the local arch height error threshold limits, a quantitative control model of interpolated distance parameters within the geodetic line plotting arch height error threshold limits is also established. A rapid plotting algorithm of the geodetic line with arch height error threshold under Mercator projection is proposed in this paper. The experimental results show that the algorithm can realize the rapid plotting of geodetic lines in any length and any latitude and longitude range, and the precision is controlled within the specified threshold range.

Development of an Image De-Noising Method in Preparation for the Surface Water and Ocean Topography Satellite Mission

In the near future, the Surface Water Ocean Topography (SWOT) mission will provide images of altimetric data at kilometric resolution. This unprecedented 2-dimensional data structure will allow the estimation of geostrophy-related quantities that are essential for studying the ocean surface dynamics and for data assimilation uses. To estimate these quantities, i.e., to compute spatial derivatives of the Sea Surface Height (SSH) measurements, the uncorrelated, small-scale noise and errors expected to affect the SWOT data must be smoothed out while minimizing the loss of relevant, physical SSH information. This paper introduces a new technique for de-noising the future SWOT SSH images. The de-noising model is formulated as a regularized least-square problem with a Tikhonov regularization based on the first-, second-, and third-order derivatives of SSH. The method is implemented and compared to other, convolution-based filtering methods with boxcar and Gaussian kernels. This is performed using a large set of pseudo-SWOT data generated in the western Mediterranean Sea from a 1/60 ∘ simulation and the SWOT simulator. Based on root mean square error and spectral diagnostics, our de-noising method shows a better performance than the convolution-based methods. We find the optimal parametrization to be when only the second-order SSH derivative is penalized. This de-noising reduces the spatial scale resolved by SWOT by a factor of 2, and at 10 km wavelengths, the noise level is reduced by factors of 10 4 and 10 3 for summer and winter, respectively. This is encouraging for the processing of the future SWOT data.

Estimation of Variance and Spatial Correlation Width for Fine-Scale Measurement Error in Digital Elevation Model

In this article, we borrow from the blind noise parameter estimation (BNPE) methodology early developed in the image processing field an original and innovative no-reference approach to estimate digital elevation model (DEM) vertical error parameters without resorting to a reference DEM. The challenges associated with the proposed approach related to the physical nature of the error and its multifactor structure in DEM are discussed in detail. A suitable multivariate method is then developed for estimating the error in gridded DEM. It is built on a recently proposed vectorial BNPE method for estimating spatially correlated noise using noise informative areas and fractal Brownian motion. The new multivariate method is derived to estimate the effect of the stacking procedure and that of the epipolar line error on local (fine-scale) standard deviation and autocorrelation function width of photogrammetric DEM measurement error. Applying the new estimator to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) GDEM2 and Advanced Land Observing Satellite (ALOS) World 3D DEMs, good agreement of derived estimates with results available in the literature is evidenced. Adopted for TanDEM-X-DEM, estimates obtained agree well with the values provided in the height error map. In future works, the proposed no-reference method for analyzing DEM error can be extended to a larger number of predictors for accounting for other factors influencing remote sensing (RS) DEM accuracy.

The challenges of estimating the distribution of flight heights from telemetry or altimetry data

BackgroundGlobal positioning systems (GPS) and altimeters are increasingly used to monitor vertical space use by aerial species, a key aspect of their ecological niche, that we need to know to manage our own use of the airspace, and to protect those species. However, there are various sources of error in flight height data (“height” above ground, as opposed to “altitude” above a reference like the sea level). First the altitude is measured with a vertical error from the devices themselves. Then there is error in the ground elevation below the tracked animals, which translates into error in flight height computed as the difference between altitude and ground elevation. Finally, there is error in the horizontal position of the animals, which translates into error in the predicted ground elevation below the animals. We used controlled field trials, simulations, and the reanalysis of raptor case studies with state-space models to illustrate the effect of improper error management.ResultsErrors of a magnitude of 20 m appear in benign conditions for barometric altimeters and GPS vertical positioning (expected to be larger in more challenging context). These errors distort the shape of the distribution of flight heights, inflate the variance in flight height, bias behavioural state assignments, correlations with environmental covariates, and airspace management recommendations. Improper data filters such as removing all negative flight height records introduce several biases in the remaining dataset, and preclude the opportunity to leverage unambiguous errors to help with model fitting. Analyses that ignore the variance around the mean flight height, e.g., those based on linear models of flight height, and those that ignore the variance inflation caused by telemetry errors, lead to incorrect inferences.ConclusionThe state-space modelling framework, now in widespread use by ecologists and increasingly often automatically implemented within on-board GPS data processing algorithms, makes it possible to fit flight models directly to the output of GPS devices, with minimal data pre-selection, and to analyse the full distribution of flight heights, not just the mean. In addition to basic research about aerial niches, behaviour quantification, and environmental interactions, we highlight the applied relevance of our recommendations for airspace management and the conservation of aerial wildlife.

Wood volume errors from measured and predicted heights

Many volume functions use diameter and height as input variables. Measurement and prediction errors in heights propagate into the error of the wood volume estimate for a tree or a plot. We quantified these errors (and bias) with census data of species, heights, and stem diameters in a 1.44 ha hardwood stand in Lower Saxony (GER) dominated by beech (Fagus sylvatica L.) and with an understorey of hardwood species. We simulated simple random sampling with fixed area and variable radius plots and distorted the actual height measurements with three magnitudes of random Gaussian errors. The inventory protocol for height measurement results in a selection of three to four trees per plot, while heights for the remaining trees were predicted via two alternative models. Tree and plot level RMSE% of wood volume with a mix of measured and predicted tree heights were—across the three magnitudes of measurement errors, 18–81% greater than root-mean-squared errors obtained when all trees were measured for heights with errors. The results from this study contribute the statistical side of recommendations on the number of height measurements per forest inventory plot, where inferences on optimal numbers of height measurements will also depend on the costs.

Modeling the Optimal Baseline for a Spaceborne Bistatic SAR System to Generate DEMs

Interferometric synthetic aperture radar (InSAR) is one of the best methods for obtaining digital elevation models (DEMs). However, the problem of the uncertainty of DEM accuracy affected by the perpendicular baseline still persists, which should be as long as possible to ensure the sensitivity of the phase to the height measurement, and as small as possible to ensure a high spatial coherence. Moreover, the baseline configuration design of bistatic SAR system lacks a more detailed model for reference to generate high-precision DEM. Therefore, in this paper, the optimal baseline is modeled to maximize the accuracy of height measurement. First, we analyze the influence of system parameters on the height measurement accuracy, and a propagation model from the parameter estimation error to the elevation error is derived. Then, the phase unwrapping error (PUE) that considers the spatial baseline coherence, terrain slope and phase unwrapping effectiveness is modeled and analyzed after interferometric phase simulation and adaptive unscented Kalman filter phase unwrapping. Combining the relationship between the height error and the PUE, the optimal baseline model is obtained by statistical analysis. Finally, weighted averages are used to calculate the average slope of the complex terrain and the validity and reliability of the proposed optimal baseline model are verified by two examples of complex terrains with uniformly and nonuniformly distributed positive and negative slope angles. Moreover, the optimal baseline ranges of different terrain types are also derived for reference.

Analysis of the typhoon wave distribution simulated in WAVEWATCH- III model in the context of Kuroshio and wind-induced current

To investigate the relationship between surface currents and wave distributions in typhoons, we took the Typhoon Talim in 2017 as a case, and found that the track of the typhoon winds up to 50 m/s was almost consistent with the Kuroshio track, particularly from September 13 to 16, 2017. The surface current data, derived from the NCEP Climate Forecast System Version 2 (CFSv2) from the National Center of Atmospheric Research (NCAR), revealed that the speed of the wind-induced current exceeded that of the Kuroshio in the region with the maximum wind speed. In this study, was utilized a third-generation numeric wave model, WAVEWATCH-III (the latest version 5.16), developed by the National Oceanic and Atmospheric Administration (NOAA), to simulate the wave fields of Typhoon Talim using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis wind data in 0.125°×0.125° grid as the forcing field. We found that the root-mean-square error (RMSE) of the significant wave height (SWH) was 0.34 m when validated against measurements from altimeter Jason-2. In addition, we discovered that the SWH had a similar tendency to the change in the surface current speed that was approximately 0.5 m/s at the beginning of Typhoon Talim. However, the relationship became weak as the surface current speed was below 0.2 m/s. Our findings show that the distribution of typhoon waves is resulted from the interaction of surface current and the wind-sea portion of the wave system, since the distribution pattern of wind-sea is consistent with the surface current, and there is a weak relationship between surface current and swell.

Solution to the slope-height ambiguity problem in phase measuring deflectometry based on a co-axial telecentric optical path

In recent years, phase measuring deflectometry (PMD) has become a popular method to measure the shapes of specular surfaces. However, the inherent slope-height ambiguity problem, which indicates the phase of the recorded fringe pattern is determined by both the height and slope of the test surface, causes considerable ambiguity errors in the measurement results. Existing error reduction methods usually require the initial shape information of the test surface or additional equipment to assist the measurement. These requirements make measurement inflexible in some situations. In this paper, the slope-height ambiguity problem in PMD is modelled and analyzed analytically for the first time, and the system geometry requirements of minimizing the ambiguity error are carried out accordingly. To meet these requirements, a co-axis optical path setup with a telecentric imaging system is proposed. In our simulation and experiment, this system reduces the phase and height errors by up to two orders of magnitude, compared to those from the normally employed system geometry setup.

High‐Resolution Ocean Wave and Wind Characteristics Determined by the ICESat‐2 Land Surface Algorithm

AbstractThe Ice, Cloud, and land Elevation Satellite 2 (ICESat‐2) is a revolutionary remote sensing tool designed to provide high‐resolution height estimates of the Earth's surface. The photon counting LiDAR instrument onboard collects data over various surfaces and provides detailed information on regions where present observations are sparse or nonexistent. ICESat‐2 is initiating a wave of new science, and this study examines a methodology for deriving ocean surface wave and wind characteristics. Using a modified version of the ICESat‐2 land surface algorithm, individual waves are mapped along the ICESat‐2 track. Significant wave features, associated ocean wind speed, and wave energy spectra are determined from the ocean data. Validation against trustworthy data sources indicate the root mean squared error of significant wave heights is 0.3 m and is 2.4 m s−1 for wind speed. Wave spectra are more variable but peak swell and wind seas generally agree within ±8–13% of buoy estimates.

Research and Application of a Smart Monitoring System to Monitor the Deformation of a Dam and a Slope

Deformation monitoring is one of the most important means of providing feedback to ensure the safety of projects. Problems plague the existing automatic monitoring system, such as the small monitoring range of monitoring devices, the inadequate field safety protection, and the low accuracy under extreme weather conditions. These problems greatly reduce the real time and reliability of deformation monitoring data and restrict the real‐time intelligent control of engineering safety risk. In this paper, a multitype instrument‐integrated monitoring system based mainly on the total positioning station (TPS) and supplemented by the Global Navigation Satellite System (GNSS) was promoted with the methods of large field angle, data complementation, environmental perception and judgment, automatic status control, and baseline calibration‐meteorological fusion correction. The application results of Pubugou Station show that the averages of mean square error of points (APMSE) for the dam are 0.41∼1.65 mm and the averages of mean square error of height (AHMSE) are 0.42∼0.89 mm. Moreover, the APMSE and AHMSE for the slope are less than 3 mm. The maximum relative error of the TPS and GNSS data compared with the artificial monitoring data is less than 10%. Besides, the system has good overall performance and is of significant comprehensive benefits. The proposed system realizes the all‐weather real‐time monitoring of deformation and enhances the emergency response capability of special conditions in dams during the operation period.

Application Research of an Array Distributed IMU Optimization Processing Method in Personal Positioning in Large Span Blind Environment

Aiming at the long-term cumulative error inherent in pedestrian indoor inertial positioning filed, that error is mainly due to the low signal-to-noise ratio of the sensor output signal quality, the temperature drift of the gyro and the accuracy of error estimation. This paper proposes a new optimization method for array distributed MEMS-IMU: this method performs filtering and noise reduction optimization processing on inertial sensor data; The effect of temperature on the gyroscope is reduced by matrix-optimized layout, and distributed temperature compensation is performed for eight IMUs. We used MEMS-IMU worn on the foot finishing the data acquisition. Then improved a novel Pearson coefficient particle filtering method to finally complete the information fusion and positioning process in a blind environment (no beacon auxiliary information) high-precision personal large span (long time span, large distance span). The indoor positioning test results in the No. 6 Office Building of National Defense Science and Technology Park in Beijing Institute of Technology verify that the method has a horizontal error of only 6.23m (TTD ≈ 0.52%) during the horizontal span positioning which the total distance is about 1200m; In terms of vertical largespan positioning accuracy: the height error is only 4.56m (TTD ≈ 7.6%) during the positioning process of 68 minutes and 35 seconds (including intermediate stop). Compared with other multi-IMU personal positioning optimization methods, it has the advantages of high sensor data quality, small gyro temperature influence, good system error estimation accuracy and long-term long-distance positioning results. It provides a good and reliable theoretical reference for this field or extension applications.

An Investigation of Large Along-Track Errors in Extratropical Transitioning North Atlantic Tropical Cyclones in the ECMWF Ensemble

Abstract The synoptic evolution and mechanisms for the largest medium-range (72–120 h) along-track errors of tropical cyclones (TC) are investigated. The mean along-track errors (ATEs) of the 51-member European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble are evaluated for 393 forecasts (85 TCs) during the 2008 to 2016 North Atlantic seasons. The 27 unique forecasts within the upper quintile of most negative ATEs (i.e., slow bias greater than 500 km by 72 h) are inherently fast-moving TCs that undergo extratropical transition as they recurve and interact with a 300-hPa upstream trough and a downstream ridge. Both the trough and ridge are underamplified by only 5–10 m ~60 h before the time of largest ATE. The height errors then grow rapidly due to underpredicted 300–200-hPa potential vorticity advection by both the nondivergent wind and the irrotational wind from the TC’s outflow. Both wind components are underpredicted and result in weak biases in the trough’s developing potential vorticity gradient and associated jet streak. The underamplification of the upstream trough is exacerbated by underpredicted 700-hPa cold advection extending from beneath the trough into the TC at 48–36 h before the largest ATE. Standardized differences are consistent with the mean errors and reveal that weaker divergent outflow is driven by underpredicted near-TC precipitation, which corresponds to underpredicted 700-hPa moisture fluxes near the TC at ~108 h before the largest ATE. The ensemble member ATEs at 72–120 h generally show little correlation with their ATEs before 36 h, suggesting that initial position uncertainty is not the primary source of ATE variability later in the forecast.

Azimuth Cutoff Compensation Method for SAR Wave Observation Based on Multiview Wave Spectrum Data Fusion

Azimuth cutoff is an inherent disadvantage of synthetic aperture radar (SAR) waves observation. The waves shorter than some certain wavelength (azimuth cutoff) cannot be imaged in original form (structures) by SAR. For a single SAR observation, the problem of the azimuth cutoff for ocean waves can be resolved to some extent by cooperative observations of SAR satellites. Multiple SAR satellites are required to achieve simultaneous observation of an ocean area to obtain multiview SAR ocean wave synchronization data. Currently, these data cannot be acquired from in-orbit SARs. In this study, imaging simulations of multiview SAR ocean wave synchronization data based on small SAR satellites were carried out for the first time with X-band, 4-m resolution, stripmap mode and Single Look Complex (SLC) product. The Max Planck Institute (MPI) method was used to obtain the optimum wave spectrum of the synchronous data. The influencing factors of the azimuth cutoff wavelength were analyzed by using measured and simulated SAR data. The analysis results were used to develop a novel multiview wave spectrum data fusion method for azimuth cutoff compensation. The azimuth cutoff compensation effect was evaluated by comparing the inversion results before and after data fusion: the azimuth cutoff decreased by 9.76% on average, the root mean square error (RMSE) of the significant wave height is 0.06m, and RMSE of the mean wave period is 0.58s. The azimuth cutoff compensation method can be applied to SAR data for medium and low sea states (that is, wind speeds of 5-15 m/s). These results show that the proposed method of multiview wave spectrum data fusion effectively compensates for azimuth cutoff.

Trunk Model Establishment and Parameter Estimation for a Single Tree Using Multistation Terrestrial Laser Scanning

Parameter estimation and effective tree trunk model establishment are significant to tree biomass measurements and three-dimensional (3D) reconstruction. In this study, we proposed a trunk model establishment and parameter estimation method for a single tree through multistation terrestrial laser scanning (TLS). This approach obtains a more accurate and dense point cloud and yields several improvements. First, to correct the tree position, the angle between the trunk centreline and the vertical line was extracted to normalize the tree point clouds. Subsequently, some tree model parameters were accurately calculated. The tree height was extracted based on individual differences rather than directly adopting the Digital Elevation Model (DEM) model; The B-Spline curve fitting was added to the diameters at breast height (DBH) measure, which better determined the shape of the DBH compared with circle fitting; The CBH was measured by multi-view voxel projection instead of Single-view fixed threshold segmentation, which confirmed the position of the CBH more accurately. To highlight the effectiveness and pertinence of the proposed method, we analysed three plots that the proposed method can achieve more accurate results, where the mean relative error (MRE) of the tree height, DBH and CBH were 1.89%, 1.74% and 2.91% satisfying the accuracy standard specified by the technical indicators (±5%). The experimental results validate the trunk model accuracy and the effectiveness of the parameter measurements (close to the field measurements). The proposed method is significantly different from the accuracy of the previous method. The proposed method has the best accuracy in Multistation Terrestrial Laser Scanning. Hence the proposed method has outstanding performance in the high-precision extraction of trunk parameters and the construction of trunk models which will perform forest inventory and construction of virtual forest more accurately.

Modulation Asymmetry Suppression of Multifunction Integrated Optic Circuit by Sinking Electrode

The modulation asymmetry of a multifunction integrated optic circuit (MIOC) indicates the difference in the phase response to modulation electric fields with the same magnitude but different directions, and is partly caused by the vertical component of the modulation signal. This introduces a nonlinear phase error that is difficult to compensate in fiber optic gyroscopes (FOGs), which needs to be suppressed. In this paper, a sinking-electrode MIOC design to suppress the modulation asymmetry is proposed and verified through numerical simulations. Optimal parameters of the gap, height, side-wall angle, and center position error of the sinking electrodes are obtained on the basis of the simulation results. With the proposed method, the modulation asymmetry of MIOC can be reduced from 5 × 10 -4 rad to 1 × 10 -6 rad, thus facilitating the development of high-performance FOGs. Furthermore, compared with the traditional electrode design, the sinking-electrode design can increase the tolerance for the manufacturing process, and the design configuration can be obtained through the general process method.

Autonomous Pedestrian Altitude Estimation Inside a Multi-Story Building Assisted by Motion Recognition

Owing to autonomy and continuity, a pedestrian navigation system (PNS) has been widely deployed, which is based on the micro electro-mechanical system inertial measurement unit (MEMS-IMU) and the strapdown inertial navigation system (SINS). However, altitude information cannot be effectively obtained in this system by the double integral of vertical acceleration because of the altitude channel divergent of SINS. The study is aimed at improving the accuracy and robustness of altitude estimation through a novel method based on foot-mounted MEMS-IMU. More specifically, the proposed method exploits the adaptive network-based fuzzy inference system (ANFIS) to recognize vertical motion modes including horizontal, downstairs, and upstairs movements. Then, the pseudo height model based on both motion modes and the stair height is constructed for stair walking with different height. Finally, the pseudo measurements from the pseudo height model are integrated with the data from motion prediction through the extended Kalman filter (EKF). Experimental results show that the overall classification accuracy of ANFIS can reach up to 99.1%. Since ANFIS is utilized to assist height estimation, the cumulative height error accounts for about 1.2% over a total height of 44 m when a pedestrian walks up and down six floors without external facility and barometric pressure support. It is concluded that the ANFIS-based height estimation method can achieve better vertical positioning performance for PNS than the existing approaches in terms of accuracy and robustness.

斜入射时一定温度范围内微结构高度误差对衍射效率的影响

斜入射时一定温度范围内微结构高度误差对衍射效率的影响

Deteksi Tinggi Vegetasi di Delta Mahakam dengan Penginderaan Jauh

<strong>Detection of Vegetation Height in Mahakam Delta Using Remote Sensing. </strong>The vegetation height is a vertical distance between top of the vegetation to ground surface. Vegetation height is one of the parameters for vegetation growth. There are various methods to measure vegetation height; one of them is the use of remote sensing technology. This study aims to map vegetation height in Mahakam Delta by using height models derived from remote sensing data. Such models are Digital Surface Model (DSM) and Digital Terrain Model (DTM). DSM was generated using a combination of interferometric processing of ALOS PALSAR interferometry, X-SAR, Shuttle Radar Topography Mission (SRTM), and geodetic height of Icesat/GLAS satellite imagery. This integration technique incorporated the Digital Elevation Model (DEM) method. The geoid model used in this study was EGM 2008. The following step was the correction of height errors of DSM. Terrain correction was undertaken to convert DSM into DTM, while vegetation heights were obtained from subtraction of DSM and DTM. Vertical accuracy verification refers to a tolerance of 1.96σ (95%) or ~80 cm. In DSM, a vertical accuracy value of 60.4 cm was obtained so that the DSM is feasible for mapping with scale of 1: 10,000, while the DTM was 37 cm so it is also applicable for mapping with such scale. Based on the subtraction of DSM and DTM, the vegetation heights in Mahakam Delta varied between 0 and 64 m.

An accurate phase-height mapping algorithm by using a virtual reference plane

In the phase measurement profilometry, the phase-height mapping is to calibrate the system by the height and phase of several known planes. The four planes method, which only needs the four references, is widely used due to its least amount of data. But for its height reconstruction, a large reconstructed height error will be introduced when the phase difference is close to 0. An improved phase-height mapping method, which is to create a virtual reference plane with a known height along the original reference plane, is proposed. Then the coefficient tables a, b, c, which are capable to suit for the whole calibration space, will be calculated and can improve the accuracy of 3D object reconstruction as well as the efficiency. The experimental results show that the mapping height errors can be significantly reduced. The RMS error of the reconstructed object is less than 4.8μm with the proposed method, while that of the traditional method is 350μm.