Radar Coordinates Research Articles

Radarcoding Reference Data for SAR Training Data Creation in Radar Coordinates

Radarcoding Reference Data for SAR Training Data Creation in Radar Coordinates

Joint Communication and Radar Sensing: RF Hardware Opportunities and Challenges-A Circuits and Systems Perspective.

This paper focuses on the topic of joint communication and radar sensing (JCRS) and its applications in the scope of upcoming sixth-generation (6G) technology. While the fifth-generation applications have reached the consumer market in the last few years, JCRS has been identified as one of the key technologies for next generation networks. The role of JCRS will vary, ranging from tasks such as radar coordination, context awareness for communication, enhanced security, increased availability, and improving the resilience and trustworthiness of future networks. In this work, the niche of JCRS technology in the future 6G ecosystem, as well as several potential applications, are discussed with a focus on RF hardware. The use of centimeter (cmWave) and millimeter (mmWave) frequency spectrums in the context of JCRS system implementation have been further elaborated. After presenting the near-term application scenarios, the circuit implementation perspectives are investigated in terms of radio frequency (RF) front-end architectures, antenna implementation, and phased arrays. Different communication and radar antenna options are compared, and the best candidates are identified. The packaging options are also presented. From circuit and system perspectives, link budget and self-interference cancellation (SIC) are highlighted. Furthermore, future directions including the next steps on the path to enabling JCRS technology are presented throughout this article. Prior works focused more on physical layers and network capabilities of JCRS systems, with less focus on hardware possibilities; to fill this gap, this article aims to contribute to this exciting research topic with a holistic review of RF hardware, highlighting the diversity of applications and the available technologies to tackle the near- and long-term needs of consumer applications.

МЕТОДИКА СИНТЕЗА АЛГОРИТМА ПЕЛЕНГАЦИИ ПОСТАНОВЩИКА КОМБИНИРОВАННОЙ ИМИТИРУЮЩЕЙ И МАСКИРУЮЩЕЙ ПОМЕХИ САМОПРИКРЫТИЯ В МОНОИМПУЛЬСНЫХ ИМПУЛЬСНО-ДОПЛЕРОВСКИХ РАДИОЛОКАТОРАХ СОПРОВОЖДЕНИЯ

For meters of angular coordinates of pulse-Doppler tracking radar of escort that implement the method of amplitude instantaneous comparison of radio signals, a methodology for the synthesis of the algorithm of the diversion of the combined imitating and masking jamming (CIM) has been developed. The calculation and comparative analysis of errors of evaluating the angular coordinates of the air target of the CIM-jamming when choosing as sources of veil information: retaliatory noise interference, which leads interference and the reflected air target signal.

A Trajectory Compensation Method Considering the Car-Following Behavior for Data Missing of Millimeter-Wave Radar in Roadside Detection Applications.

Concerning roadside traffic detection applications, and to address the millimeter-wave radar's missing data problem caused by target occlusion or the absence of features in low-speed conditions, this paper proposes a trajectory compensation method regarding car-following behavior. Referring to the installation scheme of the detector, a coordinate transformation method is presented to unify the radar spatial coordinates with the road coordinates. Considering the driver's car-following behavior, the optimal velocity model (OV), full velocity difference model (FVD), and the full velocity difference and acceleration (FVDA) model are applied for tracking the vehicle's trajectory related to the movement of the vehicle ahead. Finally, a data compensation scheme is presented. Taking actual trajectory data as samples, the proposed methods are verifiably useful for compensating for missing data and reconstructing target trajectories. Statistical results of different missing data trajectories demonstrate the rationality of the application of car-following models for the missing data compensation, and the FVDA model performs well compared with the OV and FVD models.

A Geometry-Aware Consistent Constraint for Height Estimation From a Single SAR Imagery in Mountain Areas

Height estimation from a single synthetic aperture radar(SAR) imagery has shown a great potential in real-time scene understanding and environment detection. It is a mathematical ill-posed problem for that a single 2D image may be projected from multiple 3D scenes. Then, the problem is that the accuracy of height estimation from a single SAR image is not high enough without prior knowledge, especially in mountain areas. Thus, we proposes a geometry-aware consistent constraint(GACC) to improve the performance of single SAR height estimation. The simulated SAR images generated from height maps are used to establish high precision transformation between map and radar coordinates in mountain areas. The main idea of GACC is that the simulated SAR image generated from estimated height map should be consistent with the ground truth simulated SAR image. A sparse height map is included as the supplementary inputs to further improve the accuracy of estimated height maps. Comparison experiments are performed in Geermu, Huangshan and Guiyang datasets and the results show that the RMSE of the estimated height map by Unet with GACC and 0.0434% sparse height gets reduced by about 98%, 78% and 94% compared with that by Unet in the three datasets.

Material identification of construction machinery based on multisource sensor information fusion

In order to improve the recognition accuracy of construction machinery and equipment and materials in low contrast scenes, a construction machinery material recognition algorithm based on multisource sensor information fusion is proposed. In the paper, the millimeter wave radar is fused with the camera considering its strong penetration ability in rainy and foggy days and dim environments. Firstly, the spatial coordinates of radar and camera are unified by establishing a spatial fusion model of millimeter wave and camera; then the target acquired by millimeter wave is projected onto the image and the detection frame intersection and ratio model is used to generate the region of interest of the camera; finally, the improved YOLOv2 algorithm is used to identify the region of interest, and in the improved idea, the low-level information is first connected with the high-level information in multilayer depth. At the same time, a multiscale feature pyramid network structure is used to achieve recognition of objects of different scales. This model effectively reduces interference from other feature categories while improving the recognition efficiency of the system. The algorithm can effectively improve the recognition accuracy of mechanical materials in low-contrast scenes, as demonstrated by the validation of different scenes.

An Area-Based Projection Algorithm for SAR Radiometric Terrain Correction and Geocoding

This article describes a projection algorithm between radar and map coordinates based on the representation of radar samples as area elements (AEs) rather than point elements. Each AE on the map grid (geographic grid) is associated with a number of radar grid samples that intersect completely or partially the AE. The association enables the geocoding (i.e., the map projection of radar imagery) with adaptive multilooking, accurately accounting for all radar samples contributing to the geocoded elements according to topography and radar geometry. By using averaging rather than interpolation, the proposed projection does not suffer from interpolation overfitting. The area-based geocoding also enables the generation of the geocoded polarimetric covariance matrix (GCOV) and geocoded synthetic aperture radar (SAR) interferograms with adaptive multilooking. Analogously, the slant-range projection of geocoded data is improved by projecting geographic grid pixels onto the radar grid according to their corresponding location based on the radar geometry without leaving gaps. This approach is used to reduce the computation time of previously published radiometric terrain correction (RTC) algorithms, performing 3.6–6.5 times faster over multilooked data and up to 26.3 times faster over single-look data. We demonstrate the strengths of the proposed area projection (AP) algorithm for RTC and geocoding using Uninhabited Aerial Vehicle SAR (UAVSAR), Sentinel-1B, and ALOS-2/PALSAR-2 data, and evaluate the results in the context of the upcoming NASA-ISRO SAR (NISAR) mission.

Synchronization-Free RadChat for Automotive Radar Interference Mitigation

Automotive radar interference mitigation is expected to be inherent in all future ADAS and AD vehicles. Joint radar communications is a candidate technology for removing this interference by coordinating radar sensing through communication. Coordination of radars requires strict time synchronization among vehicles, and our formerly proposed protocol (RadChat) achieves this by a precise absolute time, provided by GPS clocks of vehicles. However, interference might appear if synchronization among vehicles is lost in case GPS is spoofed, satellites are blocked over short intervals, or GPS is restarted/updated. Here we present a synchronization-free version of RadChat (Sync-free RadChat), which relies on using the relative time for radar coordination, eliminating the dependency on the absolute time provided by GPS. Simulation results obtained for various use cases show that Sync-free RadChat is able to mitigate interference without degrading the radar performance.

Persistent Scatterer Interferometry in mountainous areas: advantages of working in map geometry

Abstract We compare the processing of Persistent Scatterer Interferometry data in map geometry versus their processing in slant-range/azimuth radar coordinates. In mountainous areas, using the map geometry significantly reduces the geometric distortion of radar coordinates that places scatterers that are actually widely separated in altitude in very close proximity in terms of slant-range. Processing in slant-range coordinates over mountainous regions introduces distortion in the distances used for estimation and filtering of tropospheric phase and phase unwrapping. Spatial filtering, interpolation of missing values, and phase unwrapping have better performance in map geometry because the distances between points are closer to reality. Performing these steps in a map geometry results in a more robust and more reliable processing chain.

Notes on observational and radar coordinates for localized observers

The worldline of a uniformly accelerated localized observer in Minkowski space is restricted in the Rindler wedge, where the observer can in principle arrange experiments repeatedly, and the Cauchy problem for quantum fields in that Rindler wedge can be well defined. However, the observer can still receive the signals sourced by the events behind the past horizon, and coordinatize those events in terms of some kind of observational coordinates. We construct such observational coordinates in some simple cases with the localized observers in Minkowski, de Sitter, and Schwarzschild-like spacetimes, and compare them with radar coordinates for the same observers.

Preceding Vehicle Detection Method Based on Information Fusion of Millimetre Wave Radar and Deep Learning Vision

In the preceding vehicle detection based on the fusion of millimetre wave radar and camera, in order to obtain more accurate front vehicle status, a preceding vehicle detection method based on the information fusion of millimetre wave radar and deep learning vision is proposed in this paper. In this method, millimetre wave radar and camera are used to collect the information of preceding vehicle target. Firstly, the space-time coordinates of millimetre wave radar and camera are unified by imaging principle, coordinate conversion and same frame data selection. Then millimetre wave radar senses the state of preceding vehicle and divides the region of interest (ROI) by using the aspect ratio of vehicle. The camera uses YOLOv3-tiny to the ROI, and the deep learning algorithm of neural network model achieves high precision target detection and classification. Finally, the information fusion under different conditions is carried out according to the vehicle detection results of the two sensors and their Intersection- over-Union (IoU). The experimental results show that the recognition rate of the fusion method for typical vehicles is over 90%, and more accurate vehicle information can be obtained.

Ray Curvature on a Flat Earth for Computing Virtual WSR-88D Signatures of Simulated Supercell Storms

Abstract Two accepted postulates for applications of ground-based weather radars are that Earth’s surface is a perfect sphere and that all the rays launched at low-elevation angles have the same constant small curvature. To accommodate a straight vertically launched ray, we amend the second postulate by making the ray curvature dependent on the cosine of the launch angle. A standard atmospheric stratification determines the ray-curvature value at zero launch angle. Granted this amended postulate, we develop exact formulas for ray height, ground range, and ray slope angle as functions of slant range and launch angle on the real Earth. Standard practice assumes a hypothetical equivalent magnified earth, for which the rays become straight while ray height above radar level remains virtually the same function of the radar coordinates. The real-Earth and equivalent-earth formulas for height agree to within 1 m. Our ultimate goal is to place a virtual Doppler radar within a numerical or analytical model of a supercell and compute virtual signatures of simulated storms for development and testing of new warning algorithms. Since supercell models have a flat lower boundary, we must first compute the ray curvature that preserves the height function as the earth curvature tends to zero. Using an approximate height formula, we find that keeping planetary curvature minus the ray curvature at zero launch angle constant preserves ray height to within 5 m. For standard refraction the resulting ray curvature is negative, indicating that rays bend concavely upward relative to a flat earth.

Earth and Rock-Filled Dam Monitoring by High-Resolution X-Band Interferometry: Gongming Dam Case Study

Middle-sized earth- and rock-filled dams with clay cores continue to settle by approximately 0.5–1.5% of their height for approximately 1–3 years after their construction phase. This paper investigates the use of high-resolution spaceborne Synthetic aperture Radar (SAR) interferometry to monitor this settlement process, with the case of the Gongming dam in China. The varieties of slope foreshortening and stretching in the radar coordinates are attributed to the radar’s local incidence angle and the dam’s slope heading, which are analysed in detail. Focusing on the embankment slope settlement analysis, the equations for calculating foreshortening and the line-of-sight deformation decomposition are derived in detail for the adjustment and data fusing. The scattering characteristics of different materials on the dam surface are analysed, including the grass slope, concrete slope, top road (crest), top wall, step, and ditch. According to the analysis of the precipitation data from a local meteorological station, the coherence losses on the slopes are mainly caused by surface moisture. Both the TerraSAR-X Spotlight (TSX-SL) data and the COSMO-SkyMed Strip Mode (CSK-SM) data are analysed by the stacking method to assess the slopes’ deformations. The TSX-SL data results show the highest rate of settlement as 2 cm/yr on the top of the dam slope, consistent with the clay core shrinking process. The CSK-SM data show a similar trend in the lower part of the dam slope but underestimate the deformation in the upper part of the slope.

Plane segmentation and fitting method of point clouds based on improved density clustering algorithm for laser radar

Plane segmentation and fitting method of point clouds based on improved density clustering algorithm is put forward. We proposed the plane segmentation and fitting framework, which comprises of four steps: coordinate transformation, filtering, coarse segmentation, fine segmentation, plane fitting. The global coordinates of laser radar are deduced. Abnormal points are removed using statistical filtering based on Gaussian distribution. After filtering, Point clouds are segmented roughly adopting improved density clustering algorithm with proposed threshold, which is originally related to the resolution of laser radar. The point clouds are segmented furthermore with normal vector, which could make up for shortcomings, which are over-segmentation and under-segmentation. Finally planes are fitted with normal vector and centroid point. The laser radar was designed, and plane segmentations and fitting were carried out. The experimental results show that it is effective and automatic for plane segmentation with proposed method.

Synchronization and Processing in the HITCHHIKER Bistatic SAR Experiment

The work presented in this paper describes the signal processing of raw data measured by the HITCHHIKER bistatic radar system which is the final step toward open publication of the raw radar data acquired in the hybrid (spaceborne/stationary) experiments in cooperation with the TerraSAR-X/TanDEM-X system. During the preprocessing, the data stored by the sensor are transformed to a generic dataset which can be described by a generalized signal model. Therefore, the synchronization of transmitter and receiver, the position preprocessing, and the pulse compression is performed in this step. Furthermore, the preprocessed radar data are focused in spatial domain yielding synthetic aperture radar (SAR) images in bistatic radar coordinates. Finally, the structure and format of the datasets are described along with the procedure to request them.

A real‐time automated convective and stratiform precipitation segregation algorithm in native radar coordinates

AbstractA new convective/stratiform (C/S) precipitation segregation algorithm was developed for applications with single radar volume scan data and in its native (spherical) coordinates. The new algorithm consists of two parts: the first is to find convective rainfall cores based on physical characteristics of different rainfall types, and the second is to delineate the full convective area through seeded region growing. The new scheme takes into account radar sampling characteristics and a variety of precipitation scenarios where the C/S delineation was relatively challenging. The new C/S delineation scheme has two impacts on radar quantitative precipitation estimation (QPE): (i) correctly separate convective and stratiform regions such that appropriate Ze–R relationships can be applied; (ii) correctly define the stratiform area such that a vertical profile of reflectivity (VPR) correction can be applied. The VPR correction is very important to reduce overestimation errors in radar QPEs associated with bright band. The new algorithm was tested on many events and showed improved performance over previous schemes, especially when handling strong bright band and melting graupels in stratiform precipitation. The new scheme was also tested in radar quantitative precipitation estimation (QPE) and it consistently reduced the root mean square error and mean absolute bias in the radar QPE when compared with gauges.

Multiagent meta-level control for radar coordination

It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems. In this paper, we argue that multiagent meta-level control is an effective way to determine when this adaptation process should be done and how much effort should be invested in adaptation as opposed to continuing with the current action plan. We use a reinforcement learning based local optimization algorithm within each agent to learn multiagent meta-level control agent policies in a decentralized fashion. These policies will allow each agent to adapt to changes in environmental conditions while reorganizing the underlying multiagent network when needed. We then augment the agent with a heuristic rule-based algorithm that uses information provided by the reinforcement learning algorithm in order to resolve conflicts among agent policies from a local perspective at both learning and execution stages. We evaluate this mechanism in the context of a multiagent tornado tracking application called NetRads. Empirical results show that adaptive multiagent meta-level control significantly improves the performance of the tornado tracking network for a variety of weather scenarios.

Zagreb Terminal Airspace Capacity Analysis

The paper deals with the Zagreb Terminal Airspace capacity. The basic scenario has been modelled using the RAMSPlus simulator and capacity has been calculated by using the WMSE method which takes into account the peak-hour workload based on air traffic controllers’ tasks. The problem of traffic congestion has been analyzed and several case study scenarios have been simulated. The conducted simulations have demonstrated that in the conditions of increased traffic loads (traffic demand amounting to 6% annually) the working technology and the airspace organization of Zagreb Terminal Airspace will become a restricting factor at peak-hour workloads. The new technologies in Zagreb Terminal Airspace (P-RNAV routes and airspace sectorization) will enable the reduction in air-traffic controller’s workload regarding radar vectoring, radio-telephony and coordination tasks. This should increase the airspace capacity and thus enhance the safety and orderly flow of air traffic. KEY WORDS: terminal airspace, capacity, simulation, workload, task, sectorization

Emission and null coordinates: geometrical properties and physical construction

A Relativistic Positioning System is defined by four clocks (emitters) broadcasting their proper time. Then, every event reached by the signals is naturally labeled by these four times which are the emission coordinates of this event. The coordinate hypersurfaces of the emission coordinates are the future light cones based on the emitter trajectories. For this reason the emission coordinates have been also named null coordinates or light coordinates. Nevertheless, other coordinate systems used in different relativistic contexts have the own right to be named null or light coordinates. Here we analyze when one can say that a coordinate is a null coordinate and when one can say that a coordinate system is null. Moreover, we examine the physical construction and the geometrical properties of several "null coordinate systems": the emission and the reception coordinates, the radar coordinates, and the Bondi-Sachs coordinates, among others.

Impact of Phased-Array Radar Observations over a Short Assimilation Period: Observing System Simulation Experiments Using an Ensemble Kalman Filter

Abstract The conventional Weather Surveillance Radar-1988 Doppler (WSR-88D) scans a given weather phenomenon in approximately 5 min, and past results suggest that it takes 30–60 min to establish a storm into a model assimilating these data using an ensemble Kalman filter (EnKF) data assimilation technique. Severe-weather events, however, can develop and evolve very rapidly. Therefore, assimilating observations for a 30–60-min period prior to the availability of accurate analyses may not be feasible in an operational setting. A shorter assimilation period also is desired if forecasts are produced to increase the warning lead time. With the advent of the emerging phased-array radar (PAR) technology, it is now possible to scan the same weather phenomenon in less than 1 min. Therefore, it is of interest to see if the faster scanning rate of PAR can yield improvements in storm-scale analyses and forecasts from assimilating over a shorter period of time. Observing system simulation experiments are conducted to evaluate the ability to quickly initialize a storm into a numerical model using PAR data in place of WSR-88D data. Synthetic PAR and WSR-88D observations of a splitting supercell storm are created from a storm-scale model run using a realistic volume-averaging technique in native radar coordinates. These synthetic reflectivity and radial velocity observations are assimilated into the same storm-scale model over a 15-min period using an EnKF data assimilation technique followed by a 50-min ensemble forecast. Results indicate that assimilating PAR observations at 1-min intervals over a short 15-min period yields significantly better analyses and ensemble forecasts than those produced using WSR-88D observations. Additional experiments are conducted in which the adaptive scanning capability of PAR is utilized for thunderstorms that are either very close to or far away from the radar location. Results show that the adaptive scanning capability improves the analyses and forecasts when compared with the nonadaptive PAR data. These results highlight the potential for flexible rapid-scanning PAR observations to help to quickly and accurately initialize storms into numerical models yielding improved storm-scale analyses and very short range forecasts.