Radar Angle Research Articles

Position estimation and calibration for high precision human positioning and tracking using millimeter-wave radar

In this paper, a context-based human target detection and position estimation algorithm, as well as a position calibration algorithm based on radar irradiation angle are proposed to improve the positioning accuracy, which is limited by the sparse and easily submerged characteristics of the point cloud generated by millimeter-wave radar, which leads to difficulty in achieving high-precision positioning. Furthermore, an indoor target positioning and tracking system is built using 77 GHz millimeter-wave radar to verify the proposed algorithms. The experimental results indicate that the proposed algorithms can improve the positioning accuracy both in single-person and multi-person positioning scenarios, with median positioning errors 8.7 cm (36.7% decrease) and 12.95 cm (average) respectively. Therefore, the proposed sensing method is considered as a very promising technique for designing a high precision human trajectory tracking and positioning radar system.

Airborne Elevation DBF-TOPS SAR/InSAR Method Based on LOS Motion Compensation and Channel Error Equalization

Digital beamforming (DBF) TOPS SAR in elevation is a new synthetic aperture radar (SAR) system, which has the advantage of wide swath coverage and a high signal-to-noise ratio (SNR). In this paper, considering the phase preservation demand for interferometric SAR (InSAR) processing, the complete processing chain for DBF-TOPS SAR/InSAR in elevation is proposed with a wide beam angle and channels’ amplitude and phase errors. Firstly, we analyze the airborne motion compensation method along the line-of-sight direction for TOPS SAR with squint angle. Furthermore, for the large-range beam angle of DBF, the sub-swaths division process is presented for the range-dependent radar look angle, and the sub-swaths division criterion is also given in the analytic expression. Then, the relative amplitude and phase errors’ estimation and compensation method between channels is provided in the range frequency domain based on the pivoting filter with coherence weighting, which is convenient for DBF processing and SNR improvement. Finally, the DEMs are generated under different conditions to compare the phase preservation performance. The effectiveness of the proposed processing chain is verified with both simulated data and airborne real DBF-TOPS SAR/InSAR data.

Application of multi-angle millimeter-wave radar detection in human motion behavior and micro-action recognition

Millimeter-wave radar is widely used in family safety, rehabilitation, and assisted living due to its ability to operate in all weathers and all day. To address the problem whereby the radar detection angle significantly impacts human behavior recognition, a recognition method based on multi-angle radar observation is adopted. We proposed a novel radar selection method called the energy domain ratio method to choose a radar with more sensitive features. Then, local tangent space alignment and an adaptive extreme learning machine (ELM) are presented to enhance the recognition rate of the model in a high-noise environment. A multi-angle entropy feature and an improved ELM are developed to identify human micro-motion in a low-noise indoor environment. The effect of observation distance on the recognition effect was also explored. The experimental results show that the proposed model has a more than 86% recognition rate for human behavior in outdoor scenes and a recognition accuracy of more than 98% for indoor micro-action.

Digital Polarization Programmable Metasurface for Continuous Polarization Angle Rotation and Radar Applications

Polarization angle manipulation has been a vital technic in radar applications. This paper proposes and demonstrates a digital polarization programmable metasurface for continuous polarization angle rotation and radar applications. By coding “0” and “1” elements with the two orthogonally polarized waves having 180° phase difference, the polarization angle of electromagnetic (EM) waves can be continually and arbitrarily manipulated. The designed metasurface adopts a patch-transmission and line-patch structure and integrates two polarization channels to carry out 1-bit coding. By rotating the azimuth angle of the designed metasurface mechanically, a continuous rotation of the polarization angle of the transmitted wave can be achieved. Moreover, the transmission around 9.4 GHz can reach higher than 95%. The metasurface sample with optimized structure parameters has been fabricated and tested, where the measurement agrees well with the simulation results. In addition, a radar detection experiment was implemented with an anisotropic target, demonstrating the practical use of the proposed metasurface for polarimetric radar.

Performance analysis of empirical models of sea surface reflectivity based on measured data

The empirical models of sea surface reflectivity have many categories and different applicable conditions. In order to solve the problem of how to select the best models in different environments, we make a systematic analysis of the performance of different models based on the measured data of sea surface and the meteorological observation data in the Northwest Pacific. The results show that the accuracy of the empirical models of sea surface reflectivity may be biased when only the sea state is used as the description of sea surface roughness. For low radar grazing angle, NRL and HYB models can obtain better performance. It is recommended to add a fixed offset for NRL model at medium grazing angles. Constant gamma model can get better fit at high radar grazing angle.

Ship Intention Prediction at Intersections Based on Vision and Bayesian Framework

Due to the high error frequency of the existing methods in identifying a ship’s navigational intention, accidents frequently occur at intersections. Therefore, it is urgent to improve the ability to perceive ship intention at intersections. In this paper, we propose an algorithm based on the fusion of image sequence and radar information to identify the navigation intention of ships at intersections. Some existing algorithms generally use the Automatic Identification System (AIS) to identify ship intentions but ignore the problems of AIS delay and data loss, resulting in unsatisfactory effectiveness and accuracy of intention recognition. Firstly, to obtain the relationship between radar and image, a cooperative target composed of a group of concentric circles and a central positioning radar angle reflector is designed. Secondly, the corresponding relationship of radar and image characteristic matrix is obtained after employing the RANSAC method to fit radar and image detection information; then, the homographic matrix is solved to realize radar and image data matching. Thirdly, the YOLOv5 detector is used to track the ship motion in the image sequence. The visual measurement model based on continuous object tracking is established to extract the ship motion parameters. Finally, the motion intention of the ship is predicted by integrating the extracted ship motion features with the position information of the shallow layer using a Bayesian framework. Many experiments on real data sets show that our proposed method is superior to the most advanced method for ship intention identification at intersections.

Tensor-Based Target Parameter Estimation Algorithm for FDA-MIMO Radar with Array Gain-Phase Error

As a new radar system, FDA-MIMO radar has recently developed rapidly, as it has broad prospects in angle-range estimation. Unfortunately, the performance of existing algorithms for FDA-MIMO radar is greatly degrading or even failing under the condition of array gain-phase error. This paper proposes an innovative solution to the joint angle and range estimation of FDA-MIMO radar under the condition of array gain-phase error and an estimation algorithm is developed. Moreover, the corresponding Cramér-Rao bound (CRB) is derived to evaluate the algorithm. The parallel factor (PARAFAC) decomposition technique can be utilized to calculate transmitter and receiver direction matrices. Taking advantage of receiver direction matrix, the angle estimation can be obtained. The range estimation can be estimated by transmitter direction matrix and angle estimation. To eliminate the error accumulation effect of array gain-phase error, the gain error and phase error are obtained separately. In this algorithm, the impact of gain-phase error on parameter estimation is removed and so is the error accumulation effect. Therefore, the proposed algorithm can provide excellent performance of angle-range and gain-phase error estimation. Numerical experiments prove the validity and advantages of the proposed method.

Analysis and Simulation of Low Grazing Angle X-Band Coherent Radar Sea Clutter Using Memoryless Nonlinear Transformations

Two examples of low grazing angle radar sea clutter, both well described by the compound K-distribution model, are studied. Pulse Doppler processing is applied to obtain two dimensional range-time textures for the intensity, centroid and width of the Doppler spectrum. The first example exhibits a monochromatic swell pattern, allowing phase averaging to be applied to the textures. The second example has a more typical ocean wave spectrum. The intensity textures are gamma distributed, consistent with the compound K-distribution model, but the Doppler spectrum centroid and width textures are also found to be gamma distributed. Based on this analysis, a new method for simulation of coherent radar sea clutter is proposed, where separate memoryless nonlinear transformations are applied to a simulated water surface to generate the spatially and temporally varying intensity, centroid and width of the Doppler spectrum. The method builds on the evolving Doppler spectrum model for radar sea clutter simulation and established methods for simulation of water surfaces.

Distribution Characteristics of Ground Echo Amplitude and Recognition of Signal Grazing Angle.

With the continuous advancement of electronic technology, terahertz technology has gradually been applied on radar. Since short wavelength causes severe ground clutter, this paper studies the amplitude distribution statistical characteristics of the terahertz radar clutter based on the measured data, and provides technical support for the radar clutter suppression. Clutter distribution is the function of the radar glancing angle. In order to achieve targeted suppression, in this paper, selected axial integral bispectrum (selected AIB) feature is selected as deep belief network (DBN)input to complete the radar glancing angle recognition and the network structure, network training method, robustness are analyzed also. The ground clutter amplitude distribution can follow normal distribution at 0~45° grazing angles. The Weibull distribution and G0 distribution can describe the amplitude probability density function of ground clutter at grazing angles 85° and 65°. The recognition rate of different signal grazing angles can reach 91% on three different terrains. At the same time, the wide applicability of the selected AIB feature is verified. The analysis results of ground clutter amplitude characteristics play an important role in the suppression of radar ground clutter.

DOA Estimation of a Space-limited MIMO Radar with High Degree of Freedom

Aiming at the problem of the small aperture of the traditional MIMO radar with virtual degrees of freedom, this paper designs a high degree of freedom space-limited MIMO radar. Both the transmitting and receiving elements of this radar adopt a sparse array structure. Array composition, the receiving array element is composed of a single array element and a uniform linear array. The number of virtual array elements can be realized by using array elements. Compared with the traditional sparse array MIMO radar with the same number of elements, the designed space-limited sparse array MIMO radar has a larger aperture. Experimental simulations verify the superiority of the space-limited MIMO radar angle estimation.

Mono-pulse radar angle estimation algorithm under low signal-to-noise ratio

In the case of low signal-to-noise ratio (SNR), in order to improve the angle measurement accuracy of the mono-pulse radar seeker, a target angle estimation algorithm is proposed. The algorithm takes the target angle as a state variable under the Bayesian framework, expands it to the state vector, performs state modeling and observation modeling on it, and builds a particle-based eye angle estimator, which improves the target angle estimation performance. The effectiveness of the algorithm is verified by the simulation data of the medium pulse repetition frequency radar seeker.

Simulation of AEBS Applicability by Changing Radar Detection Angle

As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.

Design of 77 GHz automotive angular radar array antenna with wide beamwidth and flat gain

A wide beam, flat gain planar array antenna based on beamforming technology is designed for automotive angular radar systems. The array antenna consists of three 1×10 series feed line arrays, which are designed by Dolph-Chebyshev antenna synthesis method with unequal spacing distribution to reduce the side lobes. In order to satisfy the needs of the automotive angle radar wide field of view (FOV), the beamforming techniques are used for the planar array antenna to broaden the beamwidth of the azimuth plane and improve the flatness of the gain. The simulation and the measured results agree well. The measured results show that the 1×10 line array sidelobe level is −19.7 dB; the 3×10 planar array antenna has a 3 dB beamwidth of 106.4°, and the azimuth gain flatness range can reach ± 45°, the maximum gain is 11.3 dBi.

Real-Time Rainfall Forecasts Based on Radar Reflectivity during Typhoons: Case Study in Southeastern Taiwan.

This study developed a real-time rainfall forecasting system that can predict rainfall in a particular area a few hours before a typhoon’s arrival. The reflectivity of nine elevation angles obtained from the volume coverage pattern 21 Doppler radar scanning strategy and ground-weather data of a specific area were used for accurate rainfall prediction. During rainfall prediction and analysis, rainfall retrievals were first performed to select the optimal radar scanning elevation angle for rainfall prediction at the current time. Subsequently, forecasting models were established using a single reflectivity and all elevation angles (10 prediction submodels in total) to jointly predict real-time rainfall and determine the optimal predicted values. This study was conducted in southeastern Taiwan and included three onshore weather stations (Chenggong, Taitung, and Dawu) and one offshore weather station (Lanyu). Radar reflectivities were collected from Hualien weather surveillance radar. The data for a total of 14 typhoons that affected the study area in 2008–2017 were collected. The gated recurrent unit (GRU) neural network was used to establish the forecasting model, and extreme gradient boosting and multiple linear regression were used as the benchmarks. Typhoons Nepartak, Meranti, and Megi were selected for simulation. The results revealed that the input data set merged with weather-station data, and radar reflectivity at the optimal elevation angle yielded optimal results for short-term rainfall forecasting. Moreover, the GRU neural network can obtain accurate predictions 1, 3, and 6 h before typhoon occurrence.

Radar data analysis in the presence of uncertainty

ABSTRACT This paper presents the designing of the V-test test for testing the randomness of angles under the neutrosophic statistics. The proposed test applies when the decision-maker is uncertain about the sample size or in the measurement of angles. The operational procedure for testing the randomness of the radar angles under an indeterminate environment is given. An example of radar data is chosen for illustration purpose. From the radar example, it is concluded that the proposed test is suitable to apply for testing the radar angles randomness when uncertainty is present. In addition, the proposed test is more efficient, flexible, and informative than the existing test under classical statistics.

Synthesis of Micro-Doppler Signatures of Human Activities From Different Aspect Angles Using Generative Adversarial Networks

In this paper, we propose to produce synthesized micro-Doppler signatures from different aspect angles through conditional generative adversarial networks (cGANs). Micro-Doppler signatures of non-rigid human body motions vary considerably as a function of the radar's aspect angle. Because the direction of the human motion can be arbitrary, a large volume of training data across diverse aspects is needed for practical target activity classification through machine learning. As measurements can require significant monetary and labor costs, the synthesis of micro-Doppler signatures can be an alternate solution. Therefore, we investigate the feasibility of data augmentation through synthesizing micro-Doppler signatures of human activities from diverse radar aspect angles with input data from a single aspect angle. For the training data, the micro-Doppler radar signatures of 12 human activities are generated from different angles ranging from 0 to 315 degrees, at 45-degree increments, through simulations. For each angle, cGANs are trained to synthesize the micro-Doppler signatures for that specific angle given micro-Doppler signatures from another angle. The output of each model is evaluated by calculating mean-square errors and structural similarity indexes between the synthesized micro-Doppler signatures and the ground-truth ones obtained from simulations. We test three different scenarios, and report the respective results.

Broadband array radar based on microwave photonic frequency multiplication and de-chirp receiving (Invited)

Microwave photonic radar enables the generation and processing of broadband radar signals, which can significantly improve the range resolution of the radar system. To improve the radar angle resolution and realize flexible beam control, combining microwave photonic radar technology with array radar technology is an inevitable development trend. Previously, the optical truth delay technology is intensively investigated to achieve squint-free beam steering in broadband phased array radars, which usually face the problems of high complexity, poor flexibility, and limited delay accuracy. In recent years, the broadband radar architecture based on microwave photonic frequency multiplication and de-chirp receiving has received extensive attention. The array radar constructed based on this technology has wide operation bandwidth while enabling real-time digital compensation and processing functions, which provides a new idea for the development of broadband array radars. In this paper, the research progress of the broadband array radar based on microwave photonic frequency multiplication and de-chirp processing was reviewed. After expounding the transceiver mechanism of microwave photonic broadband radar, the method for constructing broadband phased array radar and the performance of digital beam scanning and imaging were introduced. Then, the radar array was extended to MIMO architecture. The broadband microwave photonic MIMO radar based on optical wavelength division multiplexing technology was introduced and its performance in target detection and imaging was analyzed.

Generalized Ambiguity Function for FDA Radar Joint Range, Angle and Doppler Resolution Evaluation

Differs from conventional phased-array, frequency diverse array (FDA) employs a frequency increment across the array elements and thus produces a range-angle-dependent beampattern. This additional range dependence finds applications in target detection/localization, high-resolution synthetic aperture radar (SAR) imaging, and SAR deceptive jamming. To capture the essence behind those applications, we analyze the range, angle, and Doppler resolution capabilities of FDA radar signal via ambiguity function. As conventional ambiguity function is defined for a single-input single-output (SISO) signal, we extend it to the generalized ambiguity function for FDA radar signal, parameterized with the range, angle, and Doppler shifts of a target. Both theoretical analysis and numerical results show that the FDA radar with a large frequency increment has potentials in high-resolution ranging but will suffer from additional range ambiguity within the range bin and Doppler ambiguity. Moreover, the use of frequency increment brings FDA radar a virtual transmit aperture but decreases the directional gain.

Influence of motion characteristics of dual stealth aircraft on monopulse radar performance

In view of the difficulties to effectively evaluate the influence of penetration of dual stealth aircraft formation on monopulse radar angle tracking error under different flight speeds, the dynamic track model of the dual stealth aircraft under different navigation speeds is established for the first time, and the acquisition method of the dynamic Radar cross section of the dual stealth aircraft formation under different navigation speeds is proposed; the dynamic signal-to-noise ratio of the dual stealth aircraft under different navigation speeds is used as a reference and the model of single pulse radar angle tracking error is established. This paper analyzes the influence of the formation motion characteristics of dual stealth aircraft on the angle tracking error performance of monopulse radar. It is the first time to conclude that the acceleration of the navigation speed of dual stealth aircraft will increase the angle tracking error of monopulse radar when there is no interference.

Time Reversal Linearly Constrained Minimum Power Algorithm for Direction of Arrival Estimation in Diffuse Multipath Environments

Direction of arrival (DOA) estimation in diffuse multipath environments is a challenge for ground-based radar remote sensing applications, which has significant value in military fields, such as air defense surveillance. However, radar received echo usually contains various multipath signals caused by the reflection of complex ground or sea surface. With the introduction of multipath signals, traditional algorithms’ performance on angle estimation decreases severely. In response to this problem, the letter proposes a new time reversal (TR) algorithm used for multiple-input multiple-output (MIMO) radar angle estimation. First, the algorithm reconstructs a TR covariance matrix by multiplexing the data’s rows and columns, increasing the estimation accuracy of the TR covariance matrix. Besides, the letter applies a linearly constrained minimum power (LCMP) constraint to suppress diffuse multipath signals according to the prior knowledge of environments. Simulation results examine the improvement of estimation accuracy by the proposed algorithm, also verify the superiority of the proposed algorithm in different multipath scenarios. What’s more, the algorithm has broader applicability due to avoiding the difficulties of removing the coherence and estimating multipath number in practice.