Target Reflectivity Research Articles

High School EFL Teachers’ Continuous Professional Development: Target Needs, Reflection, And Challenges

High School EFL Teachers’ Continuous Professional Development: Target Needs, Reflection, And Challenges

Simulation of spatial coherence of laser echo light field from random rough surface in turbulent atmosphere

According to the generalized Huygens-Fresnel principle, we derive the analytical formula for the complex degree of coherence of the echo light field under the von Karman atmospheric turbulence spectrum condition. Based on split-step beam propagation method of the turbulent phase screen and the target surface model, the fold pass propagation simulation of the laser in the turbulent atmosphere is realized. The dynamic speckle characteristics on the image plane are consistent with the experimental phenomenon. Firstly, the simulation results of the complex degree of coherence and phase structure function of the mirrored reflection echo light field are compared with the theoretical values, which verifies the correctness of the algorithm. Based on this, the complex degree of coherence of the echo light field reflected by the optical rough surface is calculated and analyzed. The results show that on a double-path turbulent flow path of 1.1 km, in other words, it transmits 2.2 km in unfolded mode, the spatial coherence of the echo light field is very sensitive to the root mean square value of height. When the root-mean-square value of height is close to the wavelength, the coherence is seriously degraded. When the correlation length of the target surface is much larger than the atmospheric coherence length, the coherence length of the echo light field is relatively close to the set spatial coherence length. When the correlation length of the target surface is close to the atmospheric coherence length, the influence of the rough surface of the target on the beam coherence cannot be ignored. When the correlation length of the target surface is much smaller than the atmospheric coherence length, the target surface characteristics have a dominant influence on the echo coherence, the spatial coherence of the light field is seriously degraded, and the echo is close to incoherent light. Considering the smooth target reflection surface, the greater the strength of turbulence, the faster the complex coherence decreases with space. The atmospheric coherence diameter <inline-formula><tex-math id="M1">\begin{document}${r_0}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="14-20212420_M1.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="14-20212420_M1.png"/></alternatives></inline-formula> can be calculated further according to the complex degree of coherence. For the Pearson correlation coefficient the simulation value and theoretical value are both 0.998, which indicates that the atmospheric coherence diameter calculated by the complex degree of coherence has a high correlation with the theoretical value. This research provides a theoretical basis for the coherent detection scheme of echoes from rough surfaces in the turbulent atmosphere. The simulation algorithm extracts the target surface features by analyzing the variation of the complex coherence of laser echo signals in the turbulent atmosphere with the spatial distance, and also provides a method of using the known target surface to obtain path turbulence information.

Multipass Interferometric ISAR for Three-Dimensional Space Target Reconstruction

The 2-D inverse synthetic aperture radar (ISAR) images of space targets vary with the viewing angles and are not suitable for automatic target recognition (ATR), thus requiring 3-D reconstruction techniques. Conventional 3-D space target reconstruction techniques either use monostatic radar with incoherent processing for target retrieval or exploit multistatic radar but coherent processing for target reconstruction. In this article, we combined aspects of monostatic radar and coherent processing to investigate the coherent reconstruction of 3-D space target reflectivity with monostatic radar. Space objects periodically revisit the same ground area. Multipass interferometric synthetic aperture radar (multipass InSAR) uses repeat-pass synthetic aperture radar (SAR) acquisitions on the same ground area with a spaceborne SAR system for 3-D ground surface reconstruction. Motivated by multipass InSAR, we used multipass ISAR acquisitions on the same space target with monostatic ground radar for 3-D space target reconstruction. We proposed a multipass interferometric ISAR (multipass InISAR) algorithm that exploits inverse synthetic aperture technology for range-azimuth focusing and interferometry for the third dimension reconstruction. The elevation estimation performance of the algorithm is analyzed. Simulation results on the Tiangong-2 space lab, Jason-3 geodetic satellite, and ENVISAT remote sensing satellite validate the effectiveness of the proposed algorithm.

Learning to Remove Clutter in Real-World GPR Images Using Hybrid Data

The clutter in the ground-penetrating radar (GPR) radargram disguises or distorts subsurface target responses, which severely affects the accuracy of target detection and identification. Existing clutter removal methods either leave residual clutter or deform target responses when facing complex and irregular clutter in the real-world radargram. To tackle the challenge of clutter removal in real scenarios, a clutter-removal neural network (CR-Net) trained on a large-scale hybrid dataset is presented in this study. The CR-Net integrates residual dense blocks into the U-Net architecture to enhance its capability in clutter suppression and target reflection restoration. The combination of the mean absolute error (MAE) loss and the multi-scale structural similarity (MS-SSIM) loss is used to effectively drive the optimization of the network. To train the proposed CR-Net to remove complex and diverse clutter in real-world radargrams, the first large-scale hybrid dataset named CLT-GPR dataset containing clutter collected by different GPR systems in multiple scenarios is built. The CLT-GPR dataset significantly improves the generalizability of the network to remove clutter in real-world GPR radargrams. Extensive experimental results demonstrate that the CR-Net achieves superior performance over existing methods in removing clutter and restoring target responses in diverse real-world scenarios. Moreover, the CR-Net with its end-to-end design does not require manual parameter tuning, making it highly suitable for automatically producing clutter-free radargrams in GPR applications. The CLT-GPR dataset and the code implemented in the paper can be found at https://haihan-sun.github.io/GPR.html.

Electromagnetic Reflection Field Detection Based on TEO

Active electromagnetic detection explores targets using electromagnetic reflection field of metal objects. In view of the detection of active electromagnetic by detecting target reflection field, a Teager energy operator(TEO) is adopted to improve the electromagnetic reflection amplitude and instantaneous frequency detection method, the method of theoretical description and simulation verification has also carried out in this paper. Results show that this method is able to track the change of the single frequency signal of electromagnetic reflection field with good effect. It is also able to provide full details of the judgment to confirm the target. This method is simple and convenient for real-time processing, and has good application value.

Influence of atmospheric modeling on spectral target detection through forward modeling approach in multi-platform remote sensing data

Identifying objects or pixels of interest that are few in numbers and sparsely populated in imagery is referred to as target detection. Traditionally, the inverse modeling (IM) approach, usually a slow and computationally intensive process, is used for detecting targets using surface reflectance spectra. For the emerging online methods in remote sensing, modeling the at-sensor radiance of target material, i.e., a forward modeling (FM) approach, can be used. Compared to the IM approach, FM is better suited to online methods due to its potential for adaptation to regional atmospheric modeling. Spectral knowledge transfer of a target from a known to an unknown atmospheric condition is the primary outcome of an efficient target detection framework. However, such an endeavor requires an exhaustive assessment of the target detection process under different atmospheric models and associated uncertainties. The objective of this work is to assess the quantitative impact of atmospheric parameters on the detectability of engineered targets. Specifically, the impact of critical atmospheric parameters such as aerosol optical thickness (AOT), standard atmospheric profiles, and aerosol models are considered. For this effect, we designed a multi-platform image acquisition setup that acquired targets concurrently using a ground-based terrestrial hyperspectral imager (THI), an airborne hyperspectral imager (AVIRIS-NG), and a space-borne multispectral imager (Sentinel-2). We used a point-based spectroradiometer and pixel-based THI to collect the in-situ reference target reflectance spectra and generated a radiance spectral library by simulating TOA radiance spectra using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model. We have considered two cases of target radiance simulations, i.e., (i) corresponding to a grid of different AOT values for a predefined atmospheric and aerosol profile, and (ii) corresponding to varying combinations of atmospheric and aerosol profiles at a given AOT. The detection has been carried out using multiple target detection algorithms. Results indicate that the spectral knowledge-based targets can be detected in remote sensing data under different atmospheric model scenarios using the FM approach. A detection rate of about 75% and 50% have been consistently obtained for remote sensing data from airborne and space-borne platforms with a false alarm (FA) rate of 10-2 to 10-3 respectively. Change in the AOT across atmospheric models has resulted in decision-changing implications in the target detection modeling. The selection of the wrong atmospheric profile can potentially aggravate the number of FAs produced by a particular detection algorithm.

Topology optimization design and experimental validation of an acoustic metasurface for reflected wavefront modulation

Based on a level set-based topology optimization method, this study designs an acoustic metasurface capable of tailoring reflection wave arbitrarily. The present metasurface is composed of a periodic array of supercells and the supercell is constructed by eight inhomogeneous units possessing a full 2π reflection phase coverage with an interval of π/4. In the optimization, each unit in the supercell is designed through the topology optimization method to achieve a specific reflection phase, i.e., reaching a target reflection coefficient corresponding to the desired reflection phase. During the optimization process, the boundary of the unit is updated via solving the level set function, while the normal velocity is derived from the sensitivity analysis. The optimal unit configurations have relatively smooth and distinct boundaries and sample structures. The reflection fields of the designed optimal metasurface under normal and oblique plane wave incidences are investigated numerically and experimentally, and a generally good agreement between them is achieved. Results reveal that a desired reflection wave manipulation is realized by the designed metasurface based on diffraction theory, demonstrating the effectiveness and efficiency of the present topology optimization design method. Furthermore, applications of these optimal units to acoustic flat focusing and acoustic self-bending beam generation are successfully demonstrated by numerical simulations. The presented design approach is quite promising for metasurface design and may be generally used in a variety of metamaterials with a prescribed set of properties.

An Operational Radiometric Correction Technique for Shadow Reduction in Multispectral UAV Imagery

This study focuses on the recovery of information from shadowed pixels in RGB or multispectral imagery sensed from unmanned aerial vehicles (UAVs). The proposed technique is based on the concept that a property characterizing a given surface is its spectral reflectance, i.e., the ratio between the flux reflected by the surface and the radiant flux received by the surface, and this ratio is usually similar under direct-plus-diffuse irradiance and under diffuse irradiance when a Lambertian behavior can be assumed. Scene-dependent elements, such as trees, shrubs, man-made constructions, or terrain relief, can block part of the direct irradiance (usually sunbeams), in which part of the surface only receives diffuse irradiance. As a consequence, shadowed surfaces comprising pixels of the image created by the UAV remote sensor appear. Regardless of whether the imagery is analyzed by means of photointerpretation or digital classification methods, when the objective is to create land cover maps, it is hard to treat these areas in a coherent way in terms of the areas receiving direct and diffuse irradiance. The hypothesis of the present work is that the relationship between irradiance conditions in shadowed areas and non-shadowed areas can be determined by following classical empirical line techniques for fulfilling the objective of a coherent treatment in both kinds of areas. The novelty of the presented method relies on the simultaneous recovery of information in non-shadowed and shadowed areas by the in situ spectral reflectance measurements of characterized Lambertian targets followed by smoothing of the penumbra area. Once in the lab, firstly, we accurately detected the shadowed pixels by combining two well-known techniques for the detection of the shadowed areas: (1) using a physical approach based on the sun’s position and the digital surface model of the area covered by the imagery; and (2) the image-based approach using the histogram properties of the intensity image. In this paper, we present the benefits of the combined usage of both techniques. Secondly, we applied a fit between non-shadowed and shadowed areas by using a twin set of spectrally characterized target sets. One set was placed under direct and diffuse irradiance (non-shadowed targets), whereas the second set (with the same spectral characteristics) was placed under diffuse irradiance (shadowed targets). Assuming that the reflectance of the homologous targets of each set was the same, we approximated the diffuse incoming irradiance through an empirical line correction. The model was applied to all detected shadowed areas in the whole scene. Finally, a smoothing filter was applied to the penumbra transitions. The presented empirical method allowed the operational and coherent recovery of information from shadowed areas, which is very common in high-resolution UAV imagery.

Analysis of Imaging Internal Defects in Living Trees on Irregular Contours of Tree Trunks Using Ground-Penetrating Radar

The outer contours of living trees are often considered as a standard circle during non-destructive testing (NDT) of internal defects using ground-penetrating radar (GPR). However, the detection of classical cross-sections (circular) lacks consideration of irregular contours, making it difficult to accurately locate the radar image of the target. In this paper, we propose a method based on the image affine transformation and the Riemann mapping principle to analyze the effect of irregular detection routes on the geometric characteristics of target reflection hyperbola. First, for the similar output phenomenon in the “hyperbola fitting”, geometric analysis and numerical simulation were performed. Then, the conversion of irregular trunk radar images and physical domain radar images was implemented using the method of image affine transformation and the Riemann mapping principle. Finally, the influence of irregular detection routes on the geometry of the target reflection curve was investigated in detail through numerical simulations and actual experiments. The numerical simulation and measurement results demonstrated that the method in this study could better reflect the imaging characteristics of the target reflection hyperbola under the irregular detection pattern. This method provides assistance to further study the defects of irregular living trees and prevents the misjudgment of targets as a result of hyperbolic distortion, resulting in a greater prospect of application.

Spatiotemporal two-dimensional deconvolution beam imaging technology

A two-dimensional (2D) deconvolution beam imaging method based on distance and azimuth in active imaging sonar is proposed. First, the circular array is used to perform conventional beamforming for echo signal of each distance bin to obtain the distance and azimuth 2D acoustic image in active imaging sonar. Then, high-resolution azimuth information is obtained by using azimuth dimension deconvolved beamforming, which effectively improves the accuracy of target azimuth estimation. And the image in the distance dimension is deconvolved to obtain the impulse response function of the target reflection and accurately estimate the time delay of target reflection or distance information and produces high-resolution imaging results. Finally, the proposed method is validated by simulation and data, which show that the 2D deconvolution based on distance-azimuth has higher resolution and lower sidelobe imaging effect than the deconvolution based on the angle dimension.

Comparison of different methods of determining land surface reflectance for AOD retrieval

Determining land surface reflectance (LSR) is important for satellite retrieval of aerosol optical depth (AOD). Many studies have focused on the development of AOD retrieval through using different land surface reflectance determination algorithms. However, there is still lack of a comprehensive comparison among those algorithms. In this study, AOD retrieval algorithms with different land surface reflectance assumptions were compared and analyzed using Advanced Himawari Imager (AHI) data. The results demonstrate that the AOD retrieved by the algorithm considering the land surface bidirectional reflectance distribution function (BRDF) effects (Method 3) has a higher accuracy than that based on the dark target (Method 1) and second lowest reflectance (Method 2) methods. The overall correlation coefficient between the AOD retrievals considering land surface BRDF and AERONET AOD measurements is 0.93 and the Root Mean Square Error (RMSE) is 0.13. In addition, there are 68.91 % of AOD matchups falling within the expected error (±0.05 ± 0.2 × AOD AERONET). Method 3 shows a more robust performance than the other two methods for different seasons, normalized difference vegetation index (NDVI) values and scattering angles. It also shows the advantages of AOD retrieval in urban regions with relatively high LSR. The AOD retrievals based on Method 2 show the best agreement with MODIS 1 km AOD product, while Method 1 AODs are much closer to the MODIS 10 km AODs. The differences of annual average values of AHI AOD retrievals using different algorithms can be high to 0.13 at 11:00 (Beijing Time) over the Beijing-Tianjin-Hebei (BTH) region, which could cause a 23.6Wm-2 discrepancy when calculating the direct aerosol radiative effect (DARE) at the bottom of the atmosphere.

A Traffic Information Awareness Approach Based on Video Data and Millimeter Wave Radar Data Fusion

In order to solve the problems of using a single radar or video sensor in the traffic information detection process, such as susceptibility to environmental influences and non-intuitive target reflections, we propose a detection method using target correlation matching, target tracking, and target data fusion, and we show how to adjust the detection weights of the video sensor and radar sensor by adjusting the noise matrix parameters, which forms a flexible, simple, and nimble method. The efficient architecture allows accurate results in challenging environments. We show the effect on radar detection data and video detection data before and after adjustment. We test the proposed method by building a hardware verification platform and finally demonstrate it on video images. The experimental results show that the proposed method can significantly reduce the testing time while providing high detection rate in more environments.

Laser reflection echo signal detection and calculation under multi-attitude intersection

To improve the detection capability of laser fuze, this paper researches the laser echo signal detection method and echo power calculation method on laser fuze. From the multi-attitude intersection relation of projectile and target, we analyze the laser echo characteristics of target, set up the modeling of laser echo power by using the finite element meshing method. Taking into account the parameters of yaw angle and pitch angle and roll angle, we derive the target reflection laser echo power calculation function by combining the non-Lambertian and bidirectional reflection function of target's surface, establish the target detection probability calculation model. According to the established laser echo signal and echo power calculation function, we calculate the laser echo power and detection probability under the multi-attitude intersection conditions and different detection distances. Through simulation tests, the test result accords with the theoretical model.

Evolvement of interpretation capacities of seismic measurements in mining of water-soluble minerals

The current development level of geophysical methods for mining monitoring of water-soluble mineral deposits provides opportunities to control the growing variety of potentially hazardous geological and mining conditions, to identify the critical states of rock mass and to monitor the emergency facilities. Seismic surveys for solving the specified problems have proven to be a highly informative method for studying the structural features and properties of productive and waterprotective overburden strata, which has a high information richness of the recorded data. The main set of parameters for the interpretation stage of seismic exploration has been formed based on the experience in shallow seismic surveys within a potash deposit; it incl udes the target reflection times, effective and interval velocities, amplitudes, frequencies and a number of derivatives from these parameters. Improvement and adaptation of world interpretation practices in relation to the indicated seismic studies conditions provides means for increasing reliability of anomalies identification and expanding the set of typical wave ‘images’ for various kinds of inhomogeneities in a wide range of wave field realizations and its attributes. The analysis of irregular wave field component in the results of scattered waves processing, spectral decomposition and RGB-mixing is considered as an additional techniques of qualitative interpretation. An approach is proposed to determining possible fracturing in rock mass based on the variability of interval velocities. In combination with the AVO-analysis, this approach makes it possible to assess the trend of rock disintegration within the emergency facilities. The interpretation results of the areal (quasi-3D) and spatial (3D) detailed surveys of a shallow potash deposit are presented.

Design of efficient broadband extreme ultraviolet multilayer mirrors using a two-parametric merit function

Broadband reflection is a basic need in extreme ultraviolet (EUV) optics, especially for the control of a broadband source such as attosecond pulse. In this paper, we propose a design method of broadband EUV multilayer mirrors based on genetic algorithm with a two-parametric merit function. Compared with a traditional merit function, which generally employs the root-mean-square deviation of the calculated reflectivity from the target reflectivity, the proposed two-parametric merit function consisting of mean value and mean square deviation of the reflectivity can realize higher mean value and lower mean square deviation of reflectivity in the desired band, without setting the target reflectivity in advance. Using this two-parametric merit function, a broadband EUV mirror with 20.35% mean value and 0.5% mean square deviation of reflectivity is realized in the wavelength range from 60 eV to 80 eV by optimizing an aperiodic Mo/Si multilayer. In addition, the broadband EUV mirrors for different bands are designed, and their performances of broadband reflection are analyzed and compared. Our research provides a way of designing an efficient broadband multilayer with absorbing materials, and could improve the study on the control of broadband EUV sources.

Quantum illumination receiver using double homodyne detection

A quantum receiver is an essential element of quantum illumination (QI) which outperforms its classical counterpart, called classical-illumination (CI). However, there are only few proposals for realizable quantum receiver, which exploits nonlinear effects leading to increasing the complexity of receiver setups. To compensate this, in this article, we design a quantum receiver with linear optical elements for Gaussian QI. Rather than exploiting nonlinear effect, our receiver consists of a 50:50 beam splitter and homodyne detection. Using double homodyne detection after the 50:50 beam splitter, we analyze the performance of the QI in different regimes of target reflectivity, source power, and noise level. We show that our receiver has better signal-to-noise ratio and more robust against noise than the existing simple-structured receivers.

Divergence Measures and Detection Performance for Dispersive Targets in SAR

AbstractWhen electromagnetic waves impinge on objects with complex geometries and/or internal structure, we can observe scattering that is distributed in time rather than instantaneous. To detect and characterize such targets, we build the coordinate‐delay synthetic aperture radar (cdSAR) images by adding a delay term to the standard SAR matched filter. In order to apply this approach to the case of extended targets where the image intensity and phase are subject to strong and rapid variations (the phenomenon called speckle), we sample the cdSAR image at several coordinate‐delay “points” in the vicinity of the scatterer location. The discrimination between the instantaneous and delayed targets is realized through autocorrelation analysis of this sample. Because of the statistical properties of speckle, misclassification errors are inevitable. Hence, prediction of the error rate as a function of system and target parameters becomes an important problem. While Monte Carlo simulations can generate the ensembles of data for direct calculation of the error rate, this approach is computationally demanding because of its slow convergence. In order to simplify the prediction of the error rate, we employ statistical divergence measures, namely, the Hellinger distance and Kullback‐Leibler divergence. These divergence measures are calculated directly from the theoretical models of reflectivity of extended targets that we want to distinguish. We empirically establish a linear relation between the misclassification rate and the Hellinger distance for a certain class of simple target models. This relation allows us to make predictions of the error rate without performing the Monte Carlo simulations.

A Method for Rapid Measurement of the Deformation and Spatial Attitude of Large Radar Antennas Inside Radomes

It is challenging to measure, analyze, and control the deformation and space attitude of antennas in narrow radomes through geometric measurement to ensure the accuracy of phased array radar application. In this manuscript, a method for rapid measurement of antennas by adopting the combination of photogrammetry system, laser tracker and total station was proposed. The photogrammetric method was used with a homemade auxiliary tool to measure and calculate the antenna’s deformation under different temperatures and pitch angles. Mapping relations between the instrumental coordinate systems of photogrammetry system, laser tracker and total station were established through common points, including target balls and reflectors. Coordinates of mark points on antenna surface were converted from photogrammetric coordinate system to laser tracker’s and total station’s coordinate system. Thus, antenna’s pitch angles relative to the local horizontal plane and deflection angles relative to the north of the engineering coordinate system were calculated. Planar fitting, coordinate transformation and space attitude calculation were all carried out in the Spatial Analyzer (SA) software. The photogrammetric method detected the antenna’s gravitational deformation sensitively, the maximum Root Mean Square Residual (RMSR) of the reference length was $54~\mu \text{m}$ , and that of the mark points was $59~\mu \text{m}$ , which was stably in line with its nominal accuracy. Deviations caused by coordinate transformation had no significant effect on the calculation of antenna’s spatial attitude, for the maximum deviation between the converted and measured coordinates in laser tracker’s coordinate system was 0.139 mm, and that in total station’s coordinate system was 1.037 mm, both of which were within reasonable limits of the derived theoretical maximum deviations between different instruments. As a result, the maximum deviation between the calculated value and servo system’s nominal value of antenna’s pitch angle was $59.4''$ , and that of antenna’s deflection angle was $91.87''$ . This method’s efficiency was greatly improved by about ten times compared with traditional methods through statistics and estimates.

Extrinsic Calibration of Radar Mount Position and Orientation With Multiple Target Configurations

Radars are part of the sensor suite installed on modern vehicles for environmental perception. The position and orientation of the radar must be known in order to transform the detections from the radar coordinate system to a vehicle coordinate system (VCS), which is a common requirement for multisensor fusion. In this work, 77-GHz automotive radar sensors are extrinsically calibrated by registering the radar detections of corner reflector targets with known locations of the targets in the VCS; the procedure estimates the position and orientation parameters needed to transform radar detections onto the VCS. Radar detections are noisy and very sparse; hence, an effort is put into achieving good calibration accuracy by taking advantage of multiple target configurations. Two multitarget methods are discussed; one models estimation error as white noise and averages multiple estimates, and another combines all observations to make the data points denser for a one-time global estimation. The methods are tested with both synthetic and experimental data. The synthetic data result shows that, with sparse data points per target configuration, the estimation errors obtained due to the global method tend to decay faster than those obtained due to the averaging method as the number of configurations increases. The experimental data obtained from just ten target configurations result in estimation errors of about 0.35° and $1 cm$ for the orientation and position parameters, respectively.

Dual-Cross-Polarized GPR Measurement Method for Detection and Orientation Estimation of Shallowly Buried Elongated Object

Detecting a shallowly buried and elongated object and estimating its orientation using a commonly adopted co-polarized GPR system is challenging due to the presence of strong ground clutter that masks the target reflection. A cross-polarized configuration can be used to suppress ground clutter and reveal the object reflection, but it suffers from inconsistent detection capability which significantly varies with different object orientations. To address this issue, we propose a dual-cross-polarized detection (DCPD) method which utilizes two cross-polarized antennas with a special arrangement to detect the object. The signals reflected by the object and collected by the two antennas are combined in a rotationally invariant manner to ensure both effective ground clutter suppression and consistent detection irrespective of the object orientation. In addition, we present a dual-cross-polarized orientation estimation (DCPOE) algorithm to estimate the object orientation from the two cross-polarized data. The proposed DCPOE algorithm is less affected by environmental noise and performs robust and accurate azimuth angle estimation. The effectiveness of the proposed techniques in the detection and orientation estimation and their advantages over the existing method have been demonstrated using experimental data. Comparison results show that the maximum and average errors are 22.3{\deg} and 10.9{\deg} for the Alford rotation algorithm, while those are 4.9{\deg} and 1.8{\deg} for the proposed DCPOE algorithm in the demonstrated shallowly buried object cases. The proposed techniques can be unified in a framework to facilitate the investigation and mapping of shallowly buried and elongated targets.