Effect Of Viewing Angle Research Articles

Very Long Baseline Array Observations of Parsec-scale Radio Emission in Dual Active Galactic Nuclei

It is believed that dual active galactic nuclei (AGN) form during galaxy mergers. Studying dual-AGN emission can provide valuable insights into galaxy merging and evolution. To investigate parsec-scale radio emission properties, we observed eight radio components of four selected dual-AGN systems using the Very Long Baseline Array (VLBA) at 5 GHz in multiple-phase-center mode. Among them, two compact radio components, labeled J0051+0020B and J2300-0005A, were detected clearly on parsec scales for the first time. However, the radio emission of the other six components was resolved out in the high-resolution images. We provide the values or upper limits of the brightness temperature and radio emission power, and analyze the emission origins in detail for each target. Based on their physical properties reported in this work and in the literature, we suggest that the radio emission in J0051+0020B and J2300-0005A originates primarily from compact jets, while the other six sources show more complex emission mechanisms. In addition, our VLBA observations suggest that the systematic X-ray deficit in our dual-AGN sample is likely attributed to the tidally induced effect and possibly a viewing angle effect.

The turbulent variability of accretion discs observed at high energies

ABSTRACT We use numerical stochastic-viscosity hydrodynamic simulations and new analytical results from thin disc theory to probe the turbulent variability of accretion flows, as observed at high energies. We show that the act of observing accretion discs in the Wien tail exponentially enhances small-scale temperature variability in the flow, which in a real disc will be driven by magnetohydrodynamic turbulence, to large-amplitude luminosity fluctuations (as predicted analytically). In particular, we demonstrate that discs with more spatially coherent turbulence (as might be expected of thicker discs), and relativistic discs observed at larger inclinations, show significant enhancement in their Wien tail variability. We believe that this is the first analysis of relativistic viewing angle effects on turbulent variability in the literature. Using these results, we argue that tidal disruption events represent particularly interesting systems with which to study accretion flow variability, and may in fact be the best astrophysical probes of small-scale disc turbulence. This is a result of a typical tidal disruption event disc being naturally observed in the Wien tail and likely having a somewhat thicker disc and cleaner X-ray spectrum than other sources. We argue for dedicated X-ray observational campaigns of tidal disruption events, with the aim of studying accretion flow variability.

Statistical moments of VIIRS night-time lights

ABSTRACT Annual VIIRS global night-time lights traditionally report mean radiance levels after filtering to remove moonlit and cloudy data followed by outlier removal. The mean is the first statistical moment, but there are three other statistical moments (variance, skew and kurtosis) that are currently not produced globally. In this study, we generated VIIRS day/night band multiyear and annual statistical moments for a widely dispersed set of test areas. The moments were calculated from 15 arc second nightly temporal profiles spanning 2012–2020, filtered to exclude cloudy and sunlit data, with radiance adjustments to reduce view angle and lunar illuminance effects. The moment data were examined in two ways: (1) Geospatial grids-which reveal zonation and temporal changes present in urban areas and (2) Scattergrams of moment pairs. The variance versus mean scattergram exhibits several distinct data clusters used to define five zones: core lighting, dark-erratics, mid-erratics, bright-erratics and bright and seteady. The results indicate that the information content of VIIRS night-time lights can be augmented if all four statistical moments are calculated.

Effects of Different Viewing Angles and Visual Stimuli on the Performance of MI Brain-Computer Interfaces

In this study, a paradigm is proposed for 45° viewing angle and changing stimuli-based motor imagery brain-computer interface (MI-BCI). The viewing angle from the first-person perspective can better activate mirror neurons, which can improve the process of converting participants’ subjective motive intentions into operational controls. BCI performance is influenced by factors such as user attention and rhythmic visual stimulation has been shown to modulate visual attention. 18 participants completed the two-factor MI task of three viewing angles and two visual stimulus types. The results showed that the classification accuracy was found to be 76% with a 45°viewing angle and changing stimuli, which has a positive impact on the BCI's performance as well as the participants’ focus of attention during the tasks and reduces their level of visual fatigue. The findings of this study offer helpful direction for creating future interface paradigms for MI-BCI that are more effective and user-friendly.

Land Surface Phenology Retrieval through Spectral and Angular Harmonization of Landsat-8, Sentinel-2 and Gaofen-1 Data

Land Surface Phenology is an important characteristic of vegetation, which can be informative of its response to climate change. However, satellite-based identification of vegetation transition dates is hindered by inconsistencies in different observation platforms, including band settings, viewing angles, and scale effects. Therefore, time-series data with high consistency are necessary for monitoring vegetation phenology. This study proposes a data harmonization approach that involves band conversion and bidirectional reflectance distribution function (BRDF) correction to create normalized reflectance from Landsat-8, Sentinel-2A, and Gaofen-1 (GF-1) satellite data, characterized by the same spectral and illumination-viewing angles as the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Nadir BRDF Adjusted Reflectance (NBAR). The harmonized data are then subjected to the spatial and temporal adaptive reflectance fusion model (STARFM) to produce time-series data with high spatio–temporal resolution. Finally, the transition date of typical vegetation was estimated using regular 30 m spatial resolution data. The results show that the data harmonization method proposed in this study assists in improving the consistency of different observations under different viewing angles. The fusion result of STARFM was improved after eliminating differences in the input data, and the accuracy of the remote-sensing-based vegetation transition date was improved by the fused time-series curve with the input of harmonized data. The root mean square error (RMSE) estimation of the vegetation transition date decreased by 9.58 days. We concluded that data harmonization eliminates the viewing-angle effect and is essential for time-series vegetation monitoring through improved data fusion.

Image processing improvements afford second-generation handheld optoacoustic imaging of breast cancer patients

BackgroundSince the initial breast transillumination almost a century ago, breast cancer imaging using light has been considered in different implementations aiming to improve diagnostics, minimize the number of available biopsies, or monitor treatment. However, due to strong photon scattering, conventional optical imaging yields low resolution images, challenging quantification and interpretation. Optoacoustic imaging addresses the scattering limitation and yields high-resolution visualization of optical contrast, offering great potential value for breast cancer imaging. Nevertheless, the image quality of experimental systems remains limited due to a number of factors, including signal attenuation with depth and partial view angle and motion effects, particularly in multi-wavelength measurements. MethodsWe developed data analytics methods to improve the accuracy of handheld optoacoustic breast cancer imaging, yielding second-generation optoacoustic imaging performance operating in tandem with ultrasonography. ResultsWe produced the most advanced images yet with handheld optoacoustic examinations of the human breast and breast cancer, in terms of resolution and contrast. Using these advances, we examined optoacoustic markers of malignancy, including vasculature abnormalities, hypoxia, and inflammation, on images obtained from breast cancer patients. ConclusionsWe achieved a new level of quality for optoacoustic images from a handheld examination of the human breast, advancing the diagnostic and theranostic potential of the hybrid optoacoustic-ultrasound (OPUS) examination over routine ultrasonography.

Viewing Angle Effects in Quasar Application to Cosmology

Abstract The symmetry axes of active galactic nuclei (AGNs) are randomly distributed in space, but highly inclined sources are heavily obscured and are not seen as quasars with broad emission lines. The obscuring torus geometry determines the average viewing angle, and if the torus geometry changes with the redshift, this average viewing angle will also change. Thus, the ratio between the isotropic luminosity and observed luminosity may change systematically with redshift. Therefore, if we use quasars to measure the luminosity distance by evaluating the isotropic absolute luminosity and measuring the observed flux, we can have a redshift-dependent bias that can propagate to cosmological parameters. We propose a toy model for testing the effect of viewing angle uncertainty on the measurement of the luminosity distance. The model is based on analytical description of the obscuring torus applied to one-parameter observational data. It illustrates the possible change of the torus covering factor between the two chosen redshift ranges. We have estimated the possible errors in specific cosmological parameters (H 0, Ω m ) for the flat Lambda cold dark matter cosmology if a method is calibrated at low redshift and applied to the higher redshift. The errors in the cosmological parameters due to potential dependence of the viewing angle on redshift are found to be potentially significant, and the effect will have to be accommodated in the future in all quasar-based cosmological methods. A careful systematic study of AGNs means that a viewing angle across the redshift is necessary, with the use of appropriate samples and models that uniquely determine the inclination of each source.

Larger distances from larger vehicles: effect of vehicle size, viewing side and their facia on comfort distance in virtual reality

ABSTRACT Objective: It is of critical importance to develop socially sensitive vehicles that will enhance pedestrians’ sense of comfort and safety. The current study is the first to extend these effects to vehicles, by investigating individual comfort distance in virtual reality with regard to vehicles that vary in terms of size, viewing angle and anthropomorphized emotional expression. Furthermore, we investigate the effect of individual differences in terms of height, anxiety and aggression. Method: Forty-four individuals were presented with three-dimensional stimuli of vehicle models differing in size and viewing angle in virtual reality and positioned them at the distance they felt the most comfortable with. Results: Our results show that individuals are more comfortable standing further from larger vehicles and when presented with the front versus the rear view of a vehicle. Moreover, the distance from vehicles was negatively associated with the height of the individuals. Conclusion: This paper suggests that it is important for designing self-driving and autonomous vehicles to consider that vehicle size and direction as well as pedestrian’s height may impact the comfort distance felt by pedestrians. These data have clear implications for vehicle design, including self-driving and autonomous vehicles. KEY POINTS What is already known: Individuals maintain larger distances when in front of individuals/agents than beside or behind them. Individuals provide greater physical space to larger agents (animals and/or humans). No previous study investigated the effect of vehicle size, view angle, and fascia on the comfort distance preferred by individuals as pedestrians. What it adds: Individuals are more comfortable standing further from larger vehicles. Individuals prefer to place more distance between themselves and a vehicle when seeing it from the front versus the rear. Shorter individuals adopt a larger distance from vehicles irrespective of vehicle size and viewing side.

Research on the Infrared Thermographic Detection of Concrete under Solar Heating

Infrared thermography for detecting defects in concrete structures is closely related to the heat source and the optimized method of the thermal image. Due to the limitation of the irradiation area of the heat source, it is inefficient to detect the defects in large concrete structures. In this paper, sunlight was employed as a heat source to detect the defects with different sizes and depths in concrete, and the measured infrared images were processed and optimized by an enhancement algorithm. The experimental results showed that the defects in concrete could be rapidly identified under sunlight. The effect of environment, view angle, and boundary can be eliminated by image preprocessing, and the histogram equalization algorithm can increase the detection depth of the defects. The research results can also provide a reference for the infrared detection technology of concrete under the weak heat source.

Sentinel-2 and WorldView-3 atmospheric correction and signal normalization based on ground-truth spectroradiometric measurements

Remote sensing satellite Earth Observing Systems (EOS) provide a variety of products for monitoring Earth surface processes at varying spatial and spectral resolutions. Combining information from high and medium spatial resolution images is valuable for monitoring ground cover and vegetation status in cropland, grassland, forests, and other natural settings. However, coupling information from different EOS requires compensating for atmospheric and view angle effects before integrating comparable surface reflectance (SR) values. The objectives of this study were i) to assess how different atmospheric constituents affect the atmospheric correction results in Sentinel-2 and WorldView-3 imagery, ii) to establish a relationship with field spectra measurements, and iii) to develop an empirical approach to ensure that SR values extracted from different EOS can be normalized for use in monitoring vegetation and land cover status. We compared surface reflectance values derived from Sentinel-2 images corrected with Sen2Cor, MODTRAN or FLAASH atmospheric correction approaches for the visible-to-near infrared regions. Additionally, this information was compared to SR values extracted from WorldView-3 imagery acquired from the same dates and location (Central Spain) and corrected with MODTRAN and FLAASH approaches. Assessment of the atmospheric correction was conducted by comparing satellite image SR with ground-truth spectra acquired with a FieldSpec hand-held spectroradiometer. The results emphasized the importance of using common atmospheric parameters collected from ancillary data sources (i.e. MODIS Atmosphere & Land products) to ensure a reliable SR comparison. When compared to field-collected spectral data, SR from corrected Sentinel-2 push-broom imagery showed a reliable match (<4% difference in the visible bands and <0.52% difference in the near infrared bands). However, SR imagery from the pointable WorldView-3 instrument showed significant deviation, likely resulting from the effects of steep off-nadir acquisition angles (24.6° to 39.1°) combined with surface anisotropy. The magnitude and sign of the deviation in SR differed depending on the vegetation type, wavelength and sun-surface-sensor geometry. Therefore, it was necessary to account for angular effects to ensure reliable comparisons of imagery from the different EOS. In this study, an empirical angular correction approach was developed based on calibrating each WorldView-3 band against the ground-truth spectra. This correction allowed for the accurate signal normalization of WorldView-3 and Sentinel-2 imagery SR in the visible-to-near infrared regions.

Kilonova Emission from Black Hole–Neutron Star Mergers. I. Viewing-angle-dependent Lightcurves

Abstract In this paper, we explore the viewing angle effect on black hole–neutron star (BH–NS) merger kilonova lightcurves. We extrapolate the fitting formulae for the mass and velocity of dynamical ejecta across a wide mass ratio range validated with 66 simulations and use them in kilonova lightcurve calculations. The calculated peak luminosity of a BH–NS merger kilonova is typically about a few times 1041 erg s−1, which is always ≲4.5 × 1041 erg s−1. This corresponds to AB absolute magnitudes fainter than ∼−15 mag in the optical and ∼−16 mag in the infrared. The dynamical ejecta usually contribute to the majority of the kilonova emission, as its projected photosphere area is much larger than that of the disk wind outflows. The fitted blackbody temperature and the observed multiband lightcurve shape are insensitive to the line of sight. The peak time of the observed multiband lightcurves, affected by the light-propagation effect, is related to the relative motion direction between the dynamical ejecta and the observer. The predicted peak luminosity, which changes with the projected photosphere area, only varies by a factor of ∼(2–3) (or by ∼1 mag) for different viewing angles. When taking the short-duration gamma-ray burst afterglow into account, for an on-axis geometry, the kilonova emission is usually outshone by the afterglow emission and can only be observed in the redder bands, especially in the K band at late times. Compared with GW 170817/AT 2017gfo, BH–NS merger kilonovae are optically dim but possibly infrared bright, and have lower fitting temperature at the same epoch after the merger.

Magnetar as Central Engine of Gamma-Ray Bursts: Quasi-universal Jet, Event Rate, and X-Ray Luminosity Function of Dipole Radiations

Abstract Early shallow-decaying X-ray afterglows of gamma-ray bursts (GRBs) may be attributed to the dipole radiations of newly born magnetars. Assuming that the GRB jets powered by magnetars are quasi-universal, we find that the jet structure can be parameterized as a uniform jet with a luminosity of (1σ) and an opening angle (50% confidence level), surrounding by a power-law decay component with an index of (1σ). The inferred local GRB rate is ρ = 9.6 Gpc−3 yr−1 by including both the typical GRBs and LL-GRBs as the same population. The typical viewing angle is 3.3°, and may be 20° ∼ 30° for LL-GRBs. The X-ray luminosity function of the dipole radiation wind can be empirically described by a broken power-law function with indices and broken at . In the case where the wind outflow is collimated and coaxial with the GRB jet, we find that the wind structure is similar to the GRB jet, i.e., , , and . The observed correlation between the prompt gamma-ray luminosity and X-ray luminosity of the wind may result from the viewing angle effect in such a jet–wind system. A discussion on surveys using the X-ray instruments on board the Einstein Probe mission in the soft X-ray band for the jet and wind emission is also presented.

Multi-Scale Evaluation of Drone-Based Multispectral Surface Reflectance and Vegetation Indices in Operational Conditions

Compact multi-spectral sensors that can be mounted on lightweight drones are now widely available and applied within the geo- and environmental sciences. However; the spatial consistency and radiometric quality of data from such sensors is relatively poorly explored beyond the lab; in operational settings and against other sensors. This study explores the extent to which accurate hemispherical-conical reflectance factors (HCRF) and vegetation indices (specifically: normalised difference vegetation index (NDVI) and chlorophyll red-edge index (CHL)) can be derived from a low-cost multispectral drone-mounted sensor (Parrot Sequoia). The drone datasets were assessed using reference panels and a high quality 1 m resolution reference dataset collected near-simultaneously by an airborne imaging spectrometer (HyPlant). Relative errors relating to the radiometric calibration to HCRF values were in the 4 to 15% range whereas deviations assessed for a maize field case study were larger (5 to 28%). Drone-derived vegetation indices showed relatively good agreement for NDVI with both HyPlant and Sentinel 2 products (R2 = 0.91). The HCRF; NDVI and CHL products from the Sequoia showed bias for high and low reflective surfaces. The spatial consistency of the products was high with minimal view angle effects in visible bands. In summary; compact multi-spectral sensors such as the Parrot Sequoia show good potential for use in index-based vegetation monitoring studies across scales but care must be taken when assuming derived HCRF to represent the true optical properties of the imaged surface.

Human gait recognition based on deterministic learning and knowledge fusion through multiple walking views

Deformation of gait silhouettes caused by different view angles heavily affects the performance of gait recognition. In this paper, a new method based on deterministic learning and knowledge fusion is proposed to eliminate the effect of view angle for efficient view-invariant gait recognition. First, the binarized walking silhouettes are characterized with three kinds of time-varying width parameters. The nonlinear dynamics underlying different individuals’ width parameters is effectively approximated by radial basis function (RBF) neural networks through deterministic learning algorithm. The extracted gait dynamics captures the spatio-temporal characteristics of human walking, represents the dynamics of gait motion, and is shown to be insensitive to the variance across various view angles. The learned knowledge of gait dynamics is stored in constant RBF networks and used as the gait pattern. Second, in order to handle the problem of view change no matter the variation is small or large, the learned knowledge of gait dynamics from different views is fused by constructing a deep convolutional and recurrent neural network (CRNN) model for later human identification task. This knowledge fusion strategy can take advantage of the encoded local characteristics extracted from the CNN and the long-term dependencies captured by the RNN. Experimental results show that promising recognition accuracy can be achieved.

Human Gait Recognition Based on Deterministic Learning and Data Stream of Microsoft Kinect

Gait is an important biometric technology for human identification at a distance. This study focuses on gait features obtained by Microsoft Kinect and proposes a new model-based gait recognition method by combining deterministic learning theory and the data stream of Kinect. Deterministic learning theory is employed to capture the gait dynamics underlying Kinect-based gait parameters. Spatial-temporal gait features can be represented as the gait dynamics underlying the trajectories of spatial-temporal parameters, which can implicitly reflect the temporal changes of silhouette shape. Kinematic gait features can be represented as the gait dynamics underlying the trajectories of kinematic parameters, which can represent the temporal changes of body structure and dynamics. Both spatial-temporal and kinematic cues can be used separately for gait recognition using the smallest error principle. They are fused on the decision level to improve the gait recognition performance. Additionally, we discuss how to eliminate the effect of view angle on the proposed method. The experimental results indicate that encouraging recognition accuracy can be achieved.

Evaluation of RadCalNet Output Data Using Landsat 7, Landsat 8, Sentinel 2A, and Sentinel 2B Sensors

In 2013, the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) Infrared and Visible Optical Sensors Subgroup (IVOS) established the Radiometric Calibration Network (RadCalNet), consisting of four international test sites providing automated in situ measurements and estimates of propagated top-of-atmosphere (TOA) reflectance. This work evaluates the ‘reliability’ of RadCalNet TOA reflectance data at three of these sites—RVUS, LCFR, and GONA—using Landsat 7 ETM+, Landsat 8 operational land imager (OLI), and Sentinel 2A/2B (S2A/S2B) MSI TOA reflectance data. This work identified a viewing angle effect in the MSI data at the RVUS and LCFR sites; when corrected, the overall standard deviation in relative reflectance differences decreased by approximately 2% and 0.5% at the RVUS and LCFR sites, respectively. Overall, the relative mean differences between the RadCalNet surface data and sensor data for the RVUS and GONA sites are within 5% for ETM+, OLI, and S2A MSI, with an approximately 2% higher difference in the S2B MSI data at the RVUS site. The LCFR site is different from the other two sites, with relative mean differences ranging from approximately -10% to 1%, even after performing the viewing angle effect correction on the MSI data. The data from RadCalNet are easy to acquire and use. More effort is needed to better understand the behavior at LCFR. One significant improvement on the accuracy of the RadCalNet data might be the development of a site-specific BRDF characterization and correction.

The role of viewing distance and viewing angle on referees’ decision-making performance during the FIFA World Cup 2014

ABSTRACTThe present study aims to reveal the effects of positioning on decision-making performance in top-level refereeing in association football. To this end, for all 64 matches of the FIFA World Cup 2014, potential foul-play situations were videometrically analysed in terms of the referee’s position relative to the infringement. Contrary to earlier studies, viewing angles were analysed in addition to viewing distances and error rates were considered for not only falsely whistled but also falsely non-whistled events. Moreover, direct logistic regression analysis was applied to detect position-dependent differences. For the total of 1,527 potential foul play situations, an overall low error rate of 6.9% was found. The similar numbers of total whistle (n = 52) and non-whistle errors (n = 54) reflect referees’ ability to balance both types of errors. Regarding the overall viewing-distance effect, referees were 2.58 times (95% CI 1.47–4.54) more likely to commit a whistle error at 10–15 m and 5.51 times (95% CI 1.35–22.47) more likely to commit a non-whistle error at 0–5 m, corresponding to the position ranges occurring with the highest (10–15 m: 30.3%) and lowest (0–5 m: 5.8%) frequencies. In contrast, no significant effects of viewing-angle on decision-making accuracy could be revealed.

Indoor multiple human targets localization and tracking using thermopile sensor

Thermal sensors have been widely applied for human targets in battlefield surveillance and smart housing. A low-resolution thermopile sensor—GridEye is used to localize and track indoor multiple human targets. Interpolation is introduced to increase the resolution of sensor data and Gaussian filter is designed to smooth the data. An adaptive threshold method is designed to remove non-human thermal targets and background image. The human targets are located by considering the space deployment and the viewing angle effect of GridEye. Depending on target positions and the heat signatures of human targets, the targets are associated with their respective trajectories. The experimental results have shown that multiple humans can be tracked well in the indoor environment.

Estimation of LAI in Winter Wheat from Multi-Angular Hyperspectral VNIR Data: Effects of View Angles and Plant Architecture

View angle effects present in crop canopy spectra are critical for the retrieval of the crop canopy leaf area index (LAI). In the past, the angular effects on spectral vegetation indices (VIs) for estimating LAI, especially in crops with different plant architectures, have not been carefully assessed. In this study, we assessed the effects of the view zenith angle (VZA) on relationships between the spectral VIs and LAI. We measured the multi-angular hyperspectral reflectance and LAI of two cultivars of winter wheat, erectophile (W411) and planophile (W9507), across different growing seasons. The reflectance of each angle was used to calculate a variety of VIs that have already been published in the literature as well as all possible band combinations of Normalized Difference Spectral Indices (NDSIs). The above indices, along with the raw reflectance of representative bands, were evaluated with measured LAI across the view zenith angle for each cultivar of winter wheat. Data analysis was also supported by the use of the PROSAIL (PROSPECT + SAIL) model to simulate a range of bidirectional reflectance. The study confirmed that the strength of linear relationships between different spectral VIs and LAI did express different angular responses depending on plant type. LAI–VI correlations were generally stronger in erectophile than in planophile wheat types, especially at the zenith angle where the background is expected to be more evident for erectophile type wheat. The band combinations and formulas of the indices also played a role in shaping the angular signatures of the LAI–VI correlations. Overall, off-nadir angles served better than nadir angle and narrow-band indices, especially NDSIs with combinations of a red-edge (700~720 nm) and a green band, were more useful for LAI estimation than broad-band indices for both types of winter wheat. But the optimal angles much differed between two plant types and among various VIs. High significance (R2 &gt; 0.9) could be obtained by selecting appropriate VIs and view angles on both the backward and forward scattering direction. These results from the in-situ measurements were also corroborated by the simulation analysis using the PROSAIL model. For the measured datasets, the highest coefficient was obtained by NDSI(536,720) at −35° in the backward (R2 = 0.971) and NDSI(571,707) at 55° in the forward scattering direction (R2 = 0.984) for the planophile and erectophile varieties, respectively. This work highlights the influence of view geometry and plant architecture. The identification of crop plant type is highly recommended before using remote sensing VIs for the large-scale mapping of vegetation biophysical variables.

Improvement of Ground Penetrating Radar (GPR) Data Interpretability by an Enhanced Inverse Scattering Strategy

This paper is inserted into the framework of inverse scattering with application to Ground Penetrating Radar (GPR) data and is meant to provide a method helping to apply inverse scattering algorithms to electrically large investigation domains. In particular, we focus on the depth slices that are particularly important in application on cultural heritage and propose in relationship with the depth slices a strategy that we will call “shifting zoom” that is specifically a method to mitigate the effects of the limited view angle in the linear tomographic inversion applied to GPR data. In particular, this paper is an extended version of the contribution (Persico et al. in: Proceedings of Imeko international conference on metrology for archaeology and cultural heritage, Lecce, Italy, 2017a), published in the Proceedings of the conference metrology for archaeology 2017. We propose here a validation of the shifting zoom versus experimental data gathered in a controlled test site, and we will show the effect of the shifting zoom on depth slices achieved from these data after a linear inverse scattering processing has been applied for their focusing.