Three-dimensional Radar Research Articles

Asymptotic Modeling of Three-Dimensional Radar Backscattering from Oil Slicks on Sea Surfaces

This paper presents new results of a simulation of radar backscatter from oil slick areas on a real three-dimensional sea surface, based on a physical hydrodynamic model of surface wave damping in the presence of oil films, the local equilibrium model (MLB). To solve this problem, the modelling was carried out by using the first-order small-slope approximation (SSA1) model. It presents the advantage of having a very good compromise between rapidity and accuracy of the calculation. The choice of the model is justified by solving the two-dimensional problem with several asymptotic methods and further comparing the results with a rigorous numerical method, based on the Method of Moments (MoM). Two approaches called “thin-layer” (TL) and “classical” were used to deal with the double layer (air/oil/sea) problem. The TL approach assumes that this double-layer problem can be seen locally as a Fabry–Pérot interferometer, which implies that the Kirchhoff-tangent plane approximation (KA) is valid. The classical approach consists in neglecting the presence of the oil layer for dealing with electromagnetic backscattering, which is valid for very thin oil films compared to the electromagnetic (EM) wavelength. It is shown that these two approaches have rather complementary validity domains: The TL approach is always valid for small observation angles, which makes it suitable for near nadir sensors such as altimeters, whereas the classical approach is valid for moderate observation angles, which makes it suitable for most satellite applications. The 3D modelling results are compared with C-band and X-band measured data (CSK experiment and OOW NOFO experiment) in VV polarization. The calculation takes into account that the oil film on the sea surface is mainly in an emulsion state. The results highlighted the relevance of the MLB hydrodynamic model, as well as the SSA1 EM model combined wit the classical approach, for quantifying NRCS in seas contaminated with marine oil or surfactants. The agreement is indeed very good in the X-band range.

Multi-Objective Classification of Three-Dimensional Imaging Radar Point Clouds: Support Vector Machine and PointNet

Multi-Objective Classification of Three-Dimensional Imaging Radar Point Clouds: Support Vector Machine and PointNet

Doppler Velocity Enhanced Range Migration Algorithm for High Resolution and Noise-Robust Three-Dimensional Radar Imaging

Millimeter-wave and microwave short-range radar are among the most promising environmental sensing methods, with applications to situations that are otherwise optically invisible. This paper presents a Doppler velocity-enhanced range migration algorithm (RMA) that achieves both high spatial resolution and low-complexity three-dimensional (3-D) radar imaging. In this method, we address the problem of human body recognition with motion using the assumption that the motion of different human parts generates distinct micro-Doppler variations in the radar data. These variations could not only separate the RMA images with different Doppler velocities in a coherent integration-based radar imaging process, but enhances a noise reduction effect by decomposing in the Doppler velocity space. To achieve a low complexity in 3-D imaging, we incorporate the RMA method and Doppler velocity-based data decomposition. The results of numerical and experimental tests on a realistic human phantom with a walking motion demonstrate that our method provides more informative and highly separated 3-D images, even in much low SNR situation.

Gaussian Mixture Model Parameter Optimization in Range Points Migration-Based Three-Dimensional Radar Imaging

Millimeter-wave (MMW) imaging radar is one of the major environmental sensors in recent self-driving or driver assistance systems and provides environmentally robust sensing even in optically challenging conditions. As a promising three-dimensional (3-D) radar imaging technique, this study focuses on the range points migration (RPM) method, which has advantages in terms of accuracy and low complexity. In the original RPM algorithm, the parameters are manually or empirically determined by considering the sensor configuration and target shape or distance. To address this limitation, we introduced a novel parameter optimization scheme based on the Gaussian mixture model (GMM) and the expectation maximization (EM) algorithm. In addition, we used the k-space decomposition-based parameter determination scheme to determine target shape-dependent parameter selection. The results, assuming the human body imaging scenario, showed that our proposed method retains a highly accurate target image without requiring empirical parameter selection.

Three-Dimensional High-Resolution MIMO Radar Imaging via OFDM Modulation and Unitary ESPRIT

Imaging and recognition of targets with complex maneuvers bring a new challenge to conventional radar applications. In this paper, the three-dimensional (3D) high-resolution image is attained in real-time by a Multiple-Input-Multiple-Output (MIMO) radar system with single Orthogonal-Frequency-Division-Multiplexing (OFDM) pulse. First, to build the orthogonal transmit waveform set for MIMO transmission, we utilize complex orthogonal designs (CODs) for OFDM subcarrier modulation. Based on the OFDM modulation, a preprocessing method is developed for transmit waveform separation without conventional matched filtering. The result array manifold is the Kronecker product of the steering vectors of subcarrier/transmit antenna/receive antenna uniform linear arrays (ULAs). Then, the high-resolution image of target is attained by the Multidimensional Unitary Estimation of Signal Parameters via Rotational Invariant Techniques (MD-UESPRIT) algorithm. The proposed imaging procedures include the multidimensional spatial smoothing, the unitary transform via backward-forward averaging, and the joint eigenvalue decomposition (JEVD) algorithm for automatically paired coordinates estimation. Simulation tests compare the reconstruction results with the conventional methods and analyze the estimation precision relative to signal-to-noise ratio (SNR), system parameters, and errors.

Wide-Angle Frequency-Scanning Array Antenna Using Dual-Layer Finger Connected Interdigital Capacitor Based CRLH Unit Cell

In this paper, a wide-angle frequency-scanning array antenna is presented for three-dimensional (3D) radar. Initially, a modified composite right/left-handed (CRLH) unit cell based on a dual-layer finger-connected interdigital capacitor (FCIDC) is analyzed. Compared with its conventional counterpart, the proposed unit cell eliminates the undesired high-order resonances and has a lower right/left-handed passband. Then, a broadband frequency-scanning feeding network, which has a large scanning angle, is designed using the proposed CRLH unit cell. The responses of the four output ports indicate that the network can offer desired amplitude and phase difference to scan towards both negative and positive elevation angles. To validate its performance, a tightly coupled planar quasi-Yagi antenna array is fed to synthesize an array antenna. The measured results show that the designed array antenna has an impedance bandwidth ($\vert \text{S}_{11}\vert <; -10$ dB) of 118.7% (2.55-10 GHz) and gains larger than 5dBi in the bulk of the band. Besides, the radiated beam can scan from -47° to 46° continuously when the frequency ranges from 3GHz to 9GHz.

Tensor Representation for Three-Dimensional Radar Target Imaging With Sparsely Sampled Data

Three-dimensional (3-D) radar imaging can provide additional information along elevation dimension about the target with respect to the conventional 2-D radar imaging, but usually requires a huge amount of data collected over 3-D frequency-azimuth-elevation space, which motivates us to perform 3-D imaging by using sparsely sampled data. Traditional compressive sensing (CS) based 3-D imaging methods with sparse data convert the 3-D data into a long vector, and then complete the sensing and recovery steps. This 1-D vectorized model, however, faces challenges of high computational complexity and huge memory usage and may not be viable in real applications. In this article, we solve the 3-D sparse imaging problem efficiently in a tensor way. For this aim, we firstly derive the 3-D imaging model from a tensor perspective under some assumptions. Then we review three kinds of sparse data sampling schemes that are common on the existing 3-D compressive radar imaging applications. Subsequently, with the help of prior information hidden in the radar signal, i.e., sparsity and low-rank property, we propose efficient image reconstruction algorithms for different sampling schemes to produce 3-D images with sidelobes and artifacts suppressed significantly. Finally, extensive experiments based on simulated and real-measured datasets are carried out. Results show that the proposed methods can effectively generate competitive images with small reconstruction error even when the data sampling ratio is low, which confirm the validity of proposed methods.

Layered compressive sensing reconstruction for non-scanning three-dimensional laser imaging

ABSTRACTAs an active remote-sensing technique, three-dimensional (3D) laser radar enables accurate target detection and identification. However, the resolution of obtained image is limited by the integrated level of the sensor array. In this article, we propose a layered compressive sensing reconstruction method for high-resolution 3D laser imaging. The range profile is first reconstructed by applying a designed range observation matrix to the original sampling data. According to the distribution of range values in the reconstructed range profile, the original sampling data are divided into several layers and the corresponding intensity images are reconstructed by different algorithms. The global intensity image is generated by the reconstructed intensity images with different range compensation coefficients. In our simulations based on real data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model Version 2 (ASTER GDEM V2) and Landsat-8 Operational Land Imager (OLI), the proposed method realised 3D laser imaging for complex landforms with a pixel resolution of , and reached a satisfactory performance for reconstructions of the range profile (peak signal-to-noise ratio (PSNR) = 33.08 dB, feature similarity (FSIM) = 0.9450) and the intensity image (PSNR = 20.63 dB, FSIM = 0.8893) with a subrate of 0.25.

Shore Construction Detection by Automotive Radar for the Needs of Autonomous Surface Vehicle Navigation

Autonomous surface vehicles (ASVs) are becoming more and more popular for performing hydrographic and navigational tasks. One of the key aspects of autonomous navigation is the need to avoid collisions with other objects, including shore structures. During a mission, an ASV should be able to automatically detect obstacles and perform suitable maneuvers. This situation also arises in near-coastal areas, where shore structures like berths or moored vessels can be encountered. On the other hand, detection of coastal structures may also be helpful for berthing operations. An ASV can be launched and moored automatically only if it can detect obstacles in its vicinity. One commonly used method for target detection by ASVs involves the use of laser rangefinders. The main disadvantage of this approach is that such systems perform poorly in conditions with bad visibility, such as in fog or heavy rain. Therefore, alternative methods need to be sought. An innovative approach to this task is presented in this paper, which describes the use of automotive three-dimensional radar on a floating platform. The goal of the study was to assess target detection possibilities based on a comparison with photogrammetric images obtained by an unmanned aerial vehicle (UAV). The scenarios considered focused on analyzing the possibility of detecting shore structures like berths, wooden jetties, and small houses, as well as natural objects like trees or other kinds of vegetation. The recording from the radar was integrated into a single complex radar image of shore targets. It was then compared with an orthophotomap prepared from AUV camera pictures, as well as with a map based on traditional land surveys. The possibility and accuracy of detection for various types of shore structure were statistically assessed. The results show good potential for the proposed approach—in general, objects can be detected using the radar—although there is a need for development of further signal processing algorithms.

Research on Background Knowledge Based Software Processing Method of Target Height Measurement for 3D Radar

The three-dimensional (3D) radar can detect 3D information of air targets, including range, azimuth and height. It is considered as an important equipment of the air defense detection system in various countries. The precision of target height measurement is the key challenge in radar detection due to the influences of the complex background environment of air targets. This paper considers the background knowledge during target detection. By using the background knowledge of radar position meteorological parameters and multi-dimensional radar position RAG maps etc., this paper proposes an integrated software processing method to improve the precision of target height measurement for 3D radar and designs a height confidence evaluation model to improve the fusion precision of height information in the superior command unit of the radar.

THREE-DIMENSIONAL LASER RADAR RANGE IMAGERY OF COMPLEX TARGET WITH ROUGH SURFACES

THREE-DIMENSIONAL LASER RADAR RANGE IMAGERY OF COMPLEX TARGET WITH ROUGH SURFACES

Maintenance Optimization Model for One kind of Three-Dimensional Radar Antenna Array

For three-dimensional radar, maintenance cost is high and maintenance time is difficult to be determined. What’s more, model simulation computing is significantly complex. The subject of this paper is a new generation of meter wave active, phased array 3D radar. We put forth a concept that maintenance should be done after dividing into several regions to the asymmetrical distribution planar array antenna. First, a failure model of array elements is built to analyze the influence from the element to antenna. Second, the maintenance optimization model is established. Finally, computer simulations are conducted to verify the feasibility and effectiveness of the proposed model.

Predicting a Three-Dimensional Radar Coverage Area: Introducing a new method based on propagation of radio waves

This article introduces a new algorithm for obtaining a three-dimensional (3-D) radar coverage area, which enables the calculation of a radar coverage area, as well as a viewshed of the area. Its primary use is in the visualization of wireless communication systems and land mobile radio services. The algorithm also takes into account some environmental factors that affect the wave propagation, such as the refraction of waves, reflection from a rough surface, and the curvature of the earth. The algorithm is now operational in the province of Tehran, Iran.

Target angle estimation of multifunction radar in search mode using digital beamforming technique

We propose a new target angle estimation method for a multifunction radar in search mode using the digital beamforming technique. The conventional center of mass-based method (CM method) used in mechanical scanning radar or two-dimensional digital beamforming radar is not very useful for a three-dimensional multifunction radar due to many problems. We suggest a three-beam-based angle estimation method (3B method) to reduce the target angle estimation error by the CM method. The 3B method estimates the target angle in search mode with less error than the CM method for all Swerling cases and signal-to-noise ratio.

Tracking with nonlinear measurement model by coordinate rotation transformation

A new filtering method is proposed to accurately estimate target state via decreasing the nonlinearity between radar polar measurements (or spherical measurements in three-dimensional (3D) radar) and target position in Cartesian coordinate. The degree of linearity is quantified here by utilizing correlation coefficient and Taylor series expansion. With the proposed method, the original measurements are converted from polar or spherical coordinate to a carefully chosen Cartesian coordinate system that is obtained by coordinate rotation transformation to maximize the linearity degree of the conversion function from polar/spherical to Cartesian coordinate. Then the target state is filtered along each axis of the chosen Cartesian coordinate. This method is compared with extended Kalman filter (EKF), Converted Measurement Kalman filter (CMKF), unscented Kalman filter (UKF) as well as Decoupled Converted Measurement Kalman filter (DECMKF). This new method provides highly accurate position and velocity with consistent estimation.

三维激光雷达在火炮偏离角测量中的应用

三维激光雷达在火炮偏离角测量中的应用

Formation of the Enhanced-V Infrared Cloud-Top Feature from High-Resolution Three-Dimensional Radar Observations

Abstract The responsible mechanism for the formation of the enhanced-V infrared cloud-top feature observed above tropopause-penetrating thunderstorms is not well understood. A new method for the combination of volumetric radar reflectivity from individual radars into three-dimensional composites with high vertical resolution (1 km) is introduced and used to test various formation mechanisms proposed in the literature. For analysis, a set of 89 enhanced-V storms over the eastern continental United States are identified in the 10-yr period from 2001 to 2010 using geostationary satellite data. The background atmospheric state from each storm is determined using the Interim ECMWF Re-Analysis (ERA-Interim) and radiosonde observations. In conjunction with the infrared temperature fields, analysis of the radar data in a coordinate relative to the location of the overshooting convective top and in altitudes relative to the tropopause suggests that above-anvil (stratospheric) cirrus clouds are the most likely mechanism for the formation of the enhanced V.

Optoelectronic imaging using a millimeter-wave, optically controlled, photo-injected Fresnel-zone plate antenna

We present results for a rapid, precise, and wide field-of-view scanning antenna for use at millimeter and submillimeter wavelengths, based on the photo-injected Fresnel-zone plate antenna (piFZPA) method. In this paper, we demonstrate the potential of this technology as a viable solution for a range of applications demanding real-time imagery or high flexibility and beam fidelity at these frequencies. We present proof-of-principle experiments at 94 GHz that incorporate a commercial display technology operating at visible wavelengths. The 100-mm-diameter piFZPA achieves 37-dBi directivity, excellent beam symmetry, beam steering in two dimensions over a ± 20-deg field of view, and precise beam control and repeatability. Preliminary results of a piFZPA-based, short-range, 94-GHz, three-dimensional imaging radar are also presented.

Multiple surface discrimination in three-dimensional FLASH laser radar while minimizing the effects of diffraction

The goal of this work is to develop an algorithm to enhance the utility of three-dimensional (3-D) FLASH laser radar sensors through accurate ranging to multiple surfaces per image pixel while minimizing the effects of diffraction. With this algorithm it will be possible to realize numerous enhancements over both traditional Gaussian mixture modeling and single-surface range estimation. While traditional Gaussian mixture modeling can effectively model the received pulse, we know that its shape is likely altered by optical aberrations from the imaging system and the medium through which it is imaging. Additionally, only identifying a single surface per pulse may result in the loss of valuable information about partially obscured surfaces. This algorithm enables multisurface ranging of an entire image with a single laser pulse. Ultimately, improvements realized through this new ranging algorithm when coupled with various other techniques may make 3-D FLASH LADAR more suitable for remote sensing applications. Simulation examples show that the multisurface ranging algorithm derived in this work improves range estimation over standard Gaussian mixture modeling and frame-by-frame deconvolution using the Richardson-Lucy algorithm by up to 91% and 70% respectively.

Simple three-dimensional laser radar measuring method and model reconstruction for hot heavy forgings

Dimensional measurement of hot heavy forgings is desirable to permit real-time process control, but usually it is inconvenient because of the difficulty in working with very hot workpieces. We present a new three dimensional (3D) measuring approach based on a two-dimensional laser range sensor (TLRS). First, the measurement system is obtained by assembling a TLRS, an axis of rotation, and a servo motor, which rotates the scan plane of the laser ranger sensor and lets the TLRS scan forgings in different planes. Therefore, the coordinates of forging surface points can be obtained in a sensor coordinate system (SCS). According to the transformation matrix between the SCS and measurement coordinate system (MCS), coordinates of points in different SCSs can be transferred into one fixed MCS. Hence the actual 3D models of hot heavy forgings can be reconstructed by using a triangulated irregular network and be optimized by employing improved Delaunay rules. Different parameters of forgings, such as lengths and diameters, can be measured based on the 3D model. The new method is verified by experiments in both the laboratory and the forging workshop. The experimental results indicate that it is much more practical and convenient for the real-time, onsite measurement of hot heavy forgings.