4D Characterization of Short- and Long-term Height-varying Decorrelated Forest SAR Backscattering

Pol-InSAR and 3D multibaseline SAR Tomography (Tomo-SAR) can extract rich information on complex scenarios with multiple scatterers mapped in the SAR cell, in particular for forest remote sensing. However, forest scenarios are characterized by a temporal decorrelating volume canopy scatterer, and a set of related open problems exists, in particular for Tomo-SAR techniques to be applied to spaceborne monitoring of biomass. Multipass 4D Differential Tomography (Diff-Tomo) is a promising advancement, furnishing space (height)-time signatures of multiple scatterer dynamics in the SAR cell, originally with urban applications. In this paper, to better characterize forest decorrelation phenomena impacting Tomo-SAR/Pol-InSAR, experimental results are presented of the extension of Diff-Tomo methods for analyzing vegetated scenes, to extract jointly geometric and dynamic information of forest layers, at both the long and short time scale. The Diff-Tomo enabled functionality of separation in the height dimension of different temporal coherence levels (“coherence profilingâ€) that are mixed (undiscriminated) in classical total coherence analyses is extensively applied to airborne P-band multipolarimetric data, and results of this investigation are shown. Also, first ground-based radar results are presented of an innovative profiling along the height dimension of the short-term coherence, in particular aiming to characterize the magnitudes of short-term coherence times. Their expected variability along the tree structures is confirmed for the first time

Monitoring of Tsunami/Earthquake Damages by Polarimetric Microwave Remote Sensing Technique

Polarization characterizes the vector state of EM wave. When interacting with polarized wave, rough natural surface often induces dominant surface scattering; building also presents dominant double-bounce scattering. Tsunami/earthquake causes serious destruction just by inundating the land surface and destroying the building. By analyzing the change of surface and double-bounce scattering before and after disaster, we can achieve a monitoring of damages. This constitutes one basic principle of polarimetric microwave remote sensing of tsunami/earthquake. The extraction of surface and double-bounce scattering from coherency matrix is achieved by model-based decomposition. The general four-component scattering power decomposition with unitary transformation (G4U) has been widely used in the remote sensing of tsunami/earthquake to identify surface and double-bounce scattering because it can adaptively enhance surface or double-bounce scattering. Nonetheless, the strict derivation in this chapter conveys that G4U cannot always strengthen the double-bounce scattering in urban area nor strengthen the surface scattering in water or land area unless we adaptively combine G4U and its duality for an extended G4U (EG4U). Experiment on the ALOS-PALSAR datasets of 2011 great Tohoku tsunami/earthquake demonstrates not only the outperformance of EG4U but also the effectiveness of polarimetric remote sensing in the qualitative monitoring and quantitative evaluation of tsunami/earthquake damages

Интерпретация биспектральных изображений радиолокационных широкополосных сигнатур объектов

A methodological approach to the analysis of broadband radar signatures based on the application of the theory of bispectral estimation is presented. The approach involves analyzing the phase relationships of the target scattering centers, providing the more complete account of the information contained in the frequency characteristic of the target compared to the range portrait traditionally obtained using the Fourier transform. Analysis of phase connections allows identifying scattering centers formed as a result of multiple reflections of electromagnetic waves by structural elements of the object of complex shape or by separate close-located objects within the observed scene. The geometric image of the bispectra of the radar broadband object’s signature used for analysis is a hexagon in the coordinates “longitudinal range — longitudinal range,” which allows detecting mutual connections of scattering centers spaced along the direction of the location. The proposed methodological approach was tested using a synthesized frequency characteristic of an abstract multipoint target, as well as based on electrodynamic modeling data of complex backscattering fields. The comparison of the results of identification of scattering centers obtained using a bispectral image, the range portrait and the priori information about the location object indicates the correctness of the proposed methodological approach. Neyolov V. V., Samorodov A. A., Shaldaev S. E. Bispectral Images of Radar Wideband Objects Characters Interpretation. Ural Radio Engineering Journal. 2023;7(1):72–86. (In Russ.) DOI 10.15826/urej.2023.7.1.005.В статье представлен методический подход к анализу широкополосных радиолокационных сигнатур, основанный на применении теории биспектрального оценивания. Данный подход предусматривает анализ фазовых связей центров рассеяния цели, обеспечивая тем самым более полный учет информации, содержащийся в частотной характеристике цели в сравнении с дальностным портретом, традиционно получаемым с использованием преобразования Фурье. Анализ фазовых связей позволяет идентифицировать центры рассеяния, образованные в результате множественных переотражений электромагнитных волн конструктивными элементами объекта сложной формы или отдельными близкорасположенными объектами в составе наблюдаемой сцены. Используемое для анализа геометрическое изображение биспектра радиолокационной широкополосной сигнатуры объекта локации представляет собой шестиугольник в координатах «продольная дальность — продольная дальность», позволяющий выявлять взаимные связи центров рассеяния, разнесенных вдоль направления локации. Произведена апробация предложенного методического подхода с использованием синтезированной частотной характеристики абстрактной многоточечной цели, а также на основе данных электродинамического моделирования комплексных полей обратного рассеяния тестовых объектов. Сопоставление результатов идентификации центров рассеяния, полученных с использованием биспектрального изображения, дальностного портрета и априорной информации об объекте локации свидетельствует о корректности предложенного методического подхода. Неёлов В. В., Самородов А. А., Шалдаев С. Е. Интерпретация биспектральных изображений радиолокационных широкополосных сигнатур объектов. Ural Radio Engineering Journal. 2023;7(1):72–86. DOI 10.15826/urej.2023.7.1.005

Bispectral Images of Radar Wideband Objects Characters Interpretation

Поступила: 27.01.2023. Принята в печать: 07.03.2023.Received: 27.01.2023. Accepted: 07.03.2023.В статье представлен методический подход к анализу широкополосных радиолокационных сигнатур, основанный на применении теории биспектрального оценивания. Данный подход предусматривает анализ фазовых связей центров рассеяния цели, обеспечивая тем самым более полный учет информации, содержащийся в частотной характеристике цели в сравнении с дальностным портретом, традиционно получаемым с использованием преобразования Фурье. Анализ фазовых связей позволяет идентифицировать центры рассеяния, образованные в результате множественных переотражений электромагнитных волн конструктивными элементами объекта сложной формы или отдельными близкорасположенными объектами в составе наблюдаемой сцены. Используемое для анализа геометрическое изображение биспектра радиолокационной широкополосной сигнатуры объекта локации представляет собой шестиугольник в координатах «продольная дальность — продольная дальность», позволяющий выявлять взаимные связи центров рассеяния, разнесенных вдоль направления локации. Произведена апробация предложенного методического подхода с использованием синтезированной частотной характеристики абстрактной многоточечной цели, а также на основе данных электродинамического моделирования комплексных полей обратного рассеяния тестовых объектов. Сопоставление результатов идентификации центров рассеяния, полученных с использованием биспектрального изображения, дальностного портрета и априорной информации об объекте локации свидетельствует о корректности предложенного методического подхода.A methodological approach to the analysis of broadband radar signatures based on the application of the theory of bispectral estimation is presented. The approach involves analyzing the phase relationships of the target scattering centers, providing the more complete account of the information contained in the frequency characteristic of the target compared to the range portrait traditionally obtained using the Fourier transform. Analysis of phase connections allows identifying scattering centers formed as a result of multiple reflections of electromagnetic waves by structural elements of the object of complex shape or by separate close-located objects within the observed scene. The geometric image of the bispectra of the radar broadband object’s signature used for analysis is a hexagon in the coordinates “longitudinal range — longitudinal range,” which allows detecting mutual connections of scattering centers spaced along the direction of the location. The proposed methodological approach was tested using a synthesized frequency characteristic of an abstract multipoint target, as well as based on electrodynamic modeling data of complex backscattering fields. The comparison of the results of identification of scattering centers obtained using a bispectral image, the range portrait and the priori information about the location object indicates the correctness of the proposed methodological approach

Levee Slide Detection using Synthetic Aperture Radar Magnitude and Phase

The objectives of this research are to support the development of state-of-the-art methods using remotely sensed data to detect slides or anomalies in an efficient and cost-effective manner based on the use of SAR technology. Slough or slump slides are slope failures along a levee, which leave areas of the levee vulnerable to seepage and failure during high water events. This work investigates the facility of detecting the slough slides on an earthen levee with different types of polarimetric Synthetic Aperture Radar (polSAR) imagery. The source SAR imagery is fully quad-polarimetric L-band data from the NASA Jet Propulsion Laboratory’s (JPL’s) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area encompasses a portion of the levees of the lower Mississippi river, located in Mississippi, United States. The obtained classification results reveal that the polSAR data unsupervised classification with features extraction produces more appropriate results than the unsupervised classification with no features extraction. Obviously, supervised classification methods provide better classification results compared to the unsupervised methods. The anomaly identification is good with these results and was improved with the use of a majority filter. The classification accuracy is further improved with a morphology filter. The classification accuracy is significantly improved with the use of GLCM features. The classification results obtained for all three cases (magnitude, phase, and complex data), with classification accuracies for the complex data being higher, indicate that the use of synthetic aperture radar in combination with remote sensing imagery can effectively detect anomalies or slides on an earthen levee. For all the three samples it consistently shows that the accuracies for the complex data are higher when compared to those from the magnitude and phase data alone. The tests comparing complex data features to magnitude and phase data alone, and full complex data, and use of post-processing filter, all had very high accuracy. Hence we included more test samples to validate and distinguish results

Metrics for Specification, Validation, and Uncertainty Prediction for Credibility in Simulation of Active Perception Sensor Systems

The immense effort required for the safety validation of an automated driving system of SAE level 3 or higher is known not to be feasible by real test drives alone. Therefore, simulation is key even for limited operational design domains for homologation of automated driving functions. Consequently, all simulation models used as tools for this purpose must be qualified beforehand. For this, in addition to their verification and validation, uncertainty quantification (VV&UQ) and prediction for the application domain are required for the credibility of the simulation model. To enable such VV&UQ, a particularly developed lidar sensor system simulation is utilized to present new metrics that can be used holistically to demonstrate the model credibility and -maturity for simulation models of active perception sensor systems. The holistic process towards model credibility starts with the formulation of the requirements for the models. In this context, the threshold values of the metrics as acceptance criteria are quantifiable by the relevance analysis of the cause-effect chains prevailing in different scenarios, and should intuitively be in the same unit as the simulated metric for this purpose. These relationships can be inferred via the presented aligned methods “Perception Sensor Collaborative Effect and Cause Tree” (PerCollECT) and “Cause, Effect, and Phenomenon Relevance Analysis” (CEPRA). For sample validation, each experiment must be accompanied by reference measurements, as these then serve as simulation input. Since the reference data collection is subject to epistemic as well as aleatory uncertainty, which are both propagated through the simulation in the form of input data variation, this leads to several slightly different simulation results. In the simulation of measured signals and data over time considered here, this combination of uncertainties is best expressed as superimposed cumulative distribution functions. The metric must therefore be able to handle such so-called p-boxes as a result of the large set of simulations. In the present work, the area validation metric (AVM) is selected by a detailed analysis as the best of the metrics already used and extended to be able to fulfill all the requirements. This results in the corrected AVM (CAVM), which quantifies the model scattering error with respect to the real scatter. Finally, the double validation metric (DVM) is elaborated as a double-vector of the former metric with the estimate for the model bias. The novel metric is exemplarily applied to the empirical cumulative distribution functions of lidar measurements and the p-boxes from their re-simulations. In this regard, aleatory and epistemic uncertainties are taken into account for the first time and the novel metrics are successfully established. The quantification of the uncertainties and error prediction of a sensor model based on the sample validation is also demonstrated for the first time

Advances in Automated Driving Systems

Electrification, automation of vehicle control, digitalization and new mobility are the mega-trends in automotive engineering, and they are strongly connected. While many demonstrations for highly automated vehicles have been made worldwide, many challenges remain in bringing automated vehicles to the market for private and commercial use. The main challenges are as follows: reliable machine perception; accepted standards for vehicle-type approval and homologation; verification and validation of the functional safety, especially at SAE level 3+ systems; legal and ethical implications; acceptance of vehicle automation by occupants and society; interaction between automated and human-controlled vehicles in mixed traffic; human–machine interaction and usability; manipulation, misuse and cyber-security; the system costs of hard- and software and development efforts. This Special Issue was prepared in the years 2021 and 2022 and includes 15 papers with original research related to recent advances in the aforementioned challenges. The topics of this Special Issue cover: Machine perception for SAE L3+ driving automation; Trajectory planning and decision-making in complex traffic situations; X-by-Wire system components; Verification and validation of SAE L3+ systems; Misuse, manipulation and cybersecurity; Human–machine interactions, driver monitoring and driver-intention recognition; Road infrastructure measures for the introduction of SAE L3+ systems; Solutions for interactions between human- and machine-controlled vehicles in mixed traffic