A deep learning solution for height estimation on a forested area based on Pol-TomoSAR data

Forest height and underlying terrain reconstruction is one of the main aims in dealing with forested areas. Theoretically, synthetic aperture radar tomography (TomoSAR) offers the possibility to solve the layover problem, making it possible to estimate the elevation of scatters located in the same resolution cell. This article describes a deep learning approach, named tomographic SAR neural network (TSNN), which aims at reconstructing forest and ground height using multipolarimetric multibaseline (MPMB) SAR data and light detection and ranging (LiDAR)-based data. The reconstruction of the forest and ground height is formulated as a classification problem, in which TSNN, a feedforward network, is trained using covariance matrix elements as input vectors and quantized LiDAR-based data as the reference. In our work, TSNN is trained and tested with P-band MPMB data acquired by ONERA over Paracou region of French Guiana in the frame of the European Space Agency's campaign TROPISAR and LiDAR-based data provided by the French Agricultural Research Center. The novelty of the proposed TSNN is related to its ability to estimate the height with a high agreement with LiDAR-based measurement and actual height with no requirement for phase calibration. Experimental results of different covariance window sizes are included to demonstrate that TSNN conducts height measurement with high spatial resolution and vertical accuracy outperforming the other two TomoSAR methods. Moreover, the conducted experiments on the effects of phase errors in different ranges show that TSNN has a good tolerance for small errors and is still able to precisely reconstruct forest heights

Estimation of Forest Biomass and Faraday Rotation using Ultra High Frequency Synthetic Aperture Radar

Synthetic Aperture Radar (SAR) data in the Ultra High Frequency (UHF; 300 MHz – 3 GHz)) band have been shown to be strongly dependent of forest biomass, which is a poorly estimated variable in the global carbon cycle. In this thesis UHF-band SAR data from the fairly flat hemiboreal test site Remningstorp in southern Sweden were analysed. The data were collected on several occasions with different moisture conditions during the spring of 2007. Regression models for biomass estimation on stand level (0.5-9 ha) were developed for each date on which SAR data were acquired. For L-band (centre frequency 1.3 GHz) the best estimation model was based on HV-polarized backscatter, giving a root mean squared error (rmse) between 31% and 46% of the mean biomass. For P-band (centre frequency 340 MHz), regression models including HH, HV or HH and HV backscatter gave an rmse between 18% and 27%. Little or no saturation effects were observed up to 290 t/ha for P-band. A model based on physical-optics has been developed and was used to predict HH-polarized SAR data with frequencies from 20 MHz to 500 MHz from a set of vertical trunks standing on an undulating ground surface. The model shows that ground topography is a critical issue in SAR imaging for these frequencies. A regression model for biomass estimation which includes a correction for ground slope was developed using multi-polarized P-band SAR data from Remningstorp as well as from the boreal test site Krycklan in northern Sweden. The latter test site has pronounced topographic variability. It was shown that the model was able to partly compensate for moisture variability, and that the model gave an rmse of 22-33% when trained using data from Krycklan and evaluated using data from Remningstorp. Regression modelling based on P-band backscatter was also used to estimate biomass change using data acquired in Remningstorp during the spring 2007 and during the fall 2010. The results show that biomass change can be measured with an rmse of about 15% or 20 tons/ha. This suggests that not only deforestation, but also forest growth and degradation (e.g. thinning) can be measured using P-band SAR data. The thesis also includes result on Faraday rotation, which is an ionospheric effect which can have a significant impact on spaceborne UHF-band SAR images. Faraday rotation angles are estimated in spaceborne L-band SAR data. Estimates based on distributed targets and calibration targets with high signal to clutter ratios are found to be in very good agreement. Moreover, a strong correlation with independent measurements of Total Electron Content is found, further validating the estimates

Estimation of change in forest variables using synthetic aperture radar

Large scale mapping of changes in forest variables is needed for both environmental monitoring, planning of climate actions and sustainable forest management. Remote sensing can be used in conjunction with field data to produce wall-to-wall estimates that are practically impossible to produce using traditional field surveys. Synthetic aperture radar (SAR) can observe the forest independent of sunlight, clouds, snow, or rain, providing reliable high frequency coverage. Its wavelength determines the interaction with the forest, where longer wavelengths interact with larger structures of the trees, and shorter wavelengths interact mainly with the top part of the canopy, meaning that it can be chosen to fit specific applications. This thesis contains five studies conducted on the Remningstorp test site in southern Sweden. Studies I – III predicted above ground biomass (AGB) change using long wavelength polarimetric P- (in I) and L-band (in I – III) SAR data. The differences between the bands were small in terms of prediction quality, and the HV polarization, just as for AGB state prediction, was the polarization channel most correlated with AGB change. A moisture correction for L-band data was proposed and evaluated, and it was found that certain polarimetric measures were better for predicting AGB change than all of the polarization channels together. Study IV assessed the detectability of silvicultural treatments in short wavelength TanDEM-X interferometric phase heights. In line with earlier studies, only clear cuts were unambiguously distinguishable. Study V predicted site index and stand age by fitting height development curves to time series of TanDEM-X data. Site index and age were unbiasedly predicted for untreated plots, and the RMSE would likely decrease with longer time series. When stand age was known, SI was predicted with an RMSE comparable to that of the field based measurements. In conclusion, this thesis underscores SAR data's potential for generalizable methods for estimation of forest variable changes

Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms

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A Priori Knowledge-Based Post-Doppler STAP for Traffic Monitoring with Airborne Radar

Die Verkehrsüberwachung gewinnt aufgrund des weltweiten Anstiegs der Verkehrsteilnehmer immer mehr an Bedeutung. Sicherer und effizierter Straßenverkehr erfordert detaillierte Verkehrsinformationen. Häufig sind diese lediglich stationär, räumlich stark begrenzt und meist nur auf Hauptverkehrsstraßen verfügbar. In dieser Hinsicht ist ein Ausfall des Telekommunikationsnetzes, beispielsweise im Falle einer Katastrophe, und der damit einhergehende Informationsverlust als kritisch einzustufen. Flugzeuggetragene Radarsysteme mit synthetischer Apertur (eng. Synthetic Aperture Radar - SAR) können für dieses Szenario eine Lösung darstellen, da sie großflächig hochauflösende Bilder generieren können, unabhängig von Tageslicht und Witterungsbedingungen. Sie ermöglichen aufgrund dieser Charakteristik die Detektion von Bewegtzielen am Boden (eng. ground moving target indication – GMTI). Moderne GMTI-Algorithmen und -Systeme, die prinzipiell für die Verkehrsüberwachung verwendbar sind, wurden in der Literatur bereits diskutiert. Allerdings ist die Robustheit dieser Systeme oft mit hohen Kosten, hoher Hardwarekomplexität und hohem Rechenaufwand verbunden. Diese Dissertation stellt einen neuartigen GMTI-Prozessor vor, der auf dem Radar-Mehrkanalverfahren post-Doppler space-time adaptive processing (PD STAP) basiert. Durch die Überlagerung einer Straßenkarte mit einem digitalen Höhenmodell ist es mithilfe des PD STAP möglich, Falschdetektionen zu erkennen und auszuschließen sowie die detektierten Fahrzeuge ihren korrekten Straßenpositionen zu zuordnen. Die präzisen Schätzungen von Position, Geschwindigkeit und Bewegungsrichtung der Fahrzeuge können mit vergleichsweise geringerer Hardware-Komplexität zu niedrigeren Kosten durchgeführt werden. Ferner wird im Rahmen dieser Arbeit ein effizienter Datenkalibrierungsalgorithmus erläutert, der das Ungleichgewicht zwischen den Empfangskanälen sowie die Variation des Dopplerschwerpunkts über Entfernung und Azimut korrigiert und so das Messergebnis verbessert. Darüber hinaus werden neue und automatisierte Strategien zur Erhebung von Trainingsdaten vorgestellt, die für die Schätzung der Clutter-Kovarianzmatrix wegen ihres direkten Einflusses auf die Clutter-Unterdrückung und Zieldetektion essentiell für PD STAP sind. Der neuartige PD STAP Prozessor verfügt über drei verschiedene Betriebsarten, die für militärische und zivile Anwendungen geeignet sind, darunter ein schneller Verarbeitungsalgorithmus der das Potential für eine zukünftige Echtzeit-Verkehrsüberwachung hat. Alle Betriebsarten wurden erfolgreich mit Radar-Mehrkanaldaten des flugzeuggetragenen F-SAR-Radarsensors des DLR getestet

Sensibilité des observables radars à la variabilité temporelle et à la configuration géométrique de forêts tempérées et tropicales à partir de mesure de proximité haute-résolution

L'augmentation importante de la population mondiale, et par conséquent de ses besoins, exerce une pression de plus en plus importante sur les surfaces forestières. L'outil le mieux adapté au suivi des forêts, à l'échelle du globe, est la télédétection. C'est dans ce contexte que se situe ce travail de thèse, qui vise à améliorer l'estimation des paramètres biophysiques des arbres à partir de données de télédétection. L'originalité de ce travail a été d'étudier cette estimation des paramètres biophysiques en menant plusieurs études de sensibilité avec une démarche expérimentale sur des données expérimentales et sur des données simulées. Tout d'abord, l'étude s'est portée sur des séries temporelles de mesures de diffusiométrie radar obtenues sur deux sites : l'un constitué d'un cèdre en zone tempérée et l'autre d'une parcelle de forêt tropicale. Puis, cette étude de sensibilité a été poursuivie en imageant, avec une résolution élevée, plusieurs parcelles aux configurations différentes à l'intérieur d'une forêt de pin. Enfin, des données optiques et radars simulées ont été fusionnés afin d'évaluer l'apport de la fusion de données optique et radar dans l'inversion des paramètres biophysiques.The significant increase of the world population, and therefore its needs, pushes increasingly high in forest areas. The best tool for monitoring forest across the globe is remote sensing. It is in this context that this thesis, which aims to improve the retrieval of biophysical parameters of trees from remote sensing data, takes place. The originality of this work was to study the estimation of biophysical parameters across multiple sensitivity studies on experimental data and simulated data. First, the study focused on the time series of radar scatterometry measurements obtained on two sites: one characterized by a cedar in the temperate zone and the other by a forest plot of rainforest. Then, the sensitivity analysis was continued by imaging with high resolution, several forest plots with different configurations within a pine forest. Finally, simulated radar and optical data were combined to evaluate the contribution of optical and radar data fusion in the inversion of biophysical parameters.RENNES1-Bibl. électronique (352382106) / SudocSudocFranceF

Aeronautical engineering: A cumulative index to a continuing bibliography (supplement 274)

This publication is a cumulative index to the abstracts contained in supplements 262 through 273 of Aeronautical Engineering: A Continuing Bibliography. The bibliographic series is compiled through the cooperative efforts of the American Institute of Aeronautics and Astronautics (AIAA) and the National Aeronautics and Space Administration (NASA). Seven indexes are included: subject, personal author, corporate source, foreign technology, contract number, report number, and accession number

Aeronautical engineering: A continuing bibliography with indexes (supplement 292)

This bibliography lists 675 reports, articles, and other documents recently introduced into the NASA scientific and technical information system database. Subject coverage includes the following: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Etude et modélisation des potentiels du SAR basse fréquence pour l'exploration de la sub-surface en contexte aride

La télédétection radar a connu un grand développement ces dernières années, majoritairement pour l'observation de la Terre, mais également pour l'exploration planétaire. Alors que l'essentiel des applications à ce jour concerne l'étude des surfaces, le SAR permet, sous certaines conditions d'aridité, de scruter les sous-sols et c'est cette capacité que nous avons étudié plus en détail. L'objectif de notre travail était de valider, de façon expérimentale et théorique, un ensemble de techniques et de méthodes permettant d'étudier et de caractériser le sous-sol à distance. A partir de l'étude de deux sites tests (le Pyla, France et la région de Bir Safsaf, Egypte), nos travaux ont permis de mettre en évidence des structures enfouies (interface géologique, humidité du sous-sol) par des signatures caractéristiques et d'évaluer les performances de tels systèmes, laissant entrevoir des champs d'applications nouveaux et très vastes : ressource en eau, cartographie géologique, archéologie, etc.Up to now, radar remote-sensing have been mostly used for Earth-Observation. It is now used in investigation projects on solar system bodies as well. Most of applications usually concern surfaces but, in arid conditions, the SAR can help souding and analyzing the subsurface, and we particularly focused on this ability. Using experimental and theoritical approaches, the aim of our work was to validate a set of techniques and methods in order to quantitatively study and characterize the subsurface structures. From studies performed on two test-sites (the Pyla Dune in France and the Bir Safsaf region in Egypt), we put in evidence the presence of embedded structures (geological interface, moisture) and determined their characteristics. We also estimated the penetrating performances of such systems and studied a typical signature of the subsurface moisture. Our results are of interest for a wide range of applications like water resources prospection, geological mapping, archeology, etc

Ground moving target tracking with space-time adaptive radar

Ground moving target tracking by airborne radar provides situational awareness of vehicle movements in the supervised region. Vehicles are detected by applying space time adaptive processing to the received multi channel radar data. The detections are then fed to a tracking algorithm that processes them to tracks. In literature, radar signal processing and ground target tracking are treated as two separate topics and results are not validated by experimental data. The first objective of this thesis is to provide a closer link between these fields. The second objective is to show that tracking performance can be improved by providing additional data from the radar signal processing to the tracking step. The third objective is to validate the algorithm and the performance improvement using experimental data. As a result this thesis presents a unified treatment of ground moving target tracking from radar raw data to established tracks. A complete reference algorithm for ground moving target tracking based on the Gaussian mixture probability hypothesis density filter is presented. In particular, Jacobians of the observation process are derived. They are presented in such a form that immediate implementation in a programming language is possible. In the course of this thesis a measurement campaign with the experimental radar PAMIR of Fraunhofer FHR was conducted. The experiment included two GPS equipped reference vehicles and a multitude of targets of opportunity. Tracking results obtained with this experimental data and the reference tracking algorithm of this thesis are shown. The thesis also enhances the reference target tracking algorithm by a parameter that characterizes the variance of the direction of arrival measurement of the target signal. This parameter is determined adaptively depending on the estimated signal strength and the clutter background. The major contribution with regard to this enhancement is a thorough experimental validation: Firstly, a comparison between GPS based measurements and radar based measurements of the direction of arrival shows that this variance captures the distribution of measurement errors excellently. Secondly, tracking results are compared to the GPS tracks of the ground truth vehicles. It is found that the enhanced algorithm yields superior track quality with respect to both track accuracy and track continuity.Bodenzielverfolgung mit luftgestütztem Radar liefert das Lagebild von Fahrzeug­bewegungen innerhalb des beobachteten Gebiets. Fahrzeuge werden durch die Anwendung von Raum-Zeit adaptiver Signalverarbeitung (STAP) entdeckt. Die Entdeckungen werden dann von einem Zielverfolgungsalgorithmus zu Zielspuren verarbeitet. In der Literatur werden Radarsignalverarbeitung und Zielverfolgung als zwei getrennte Forschungsfelder behandelt und die Bodenzielverfolgung wird nicht anhand von Realdaten validiert. Das erste Ziel dieser Arbeit ist, eine engere Verbindung zwischen beiden Feldern herzustellen. Das zweite Ziel ist zu zeigen, dass die Qualität der Zielverfolgung durch das Verwenden zusätzlicher, durch die Radarsignalverarbeitung gewonnene Information verbessert werden kann. Das dritte Ziel ist, die Funktionalität der Zielverfolgung und die Verbesserung der Leistung durch experimentelle Realdaten zu belegen. Somit stellt diese Arbeit eine Gesamtbehandlung der Bodenzielverfolgung von den Radar-Rohdaten bis zu Zielspuren dar. Es wird ein vollständiger, auf dem Gaussian Mixture Probability Hypothesis Density Filter basierender Referenzalgorithmus für die Bodenzielverfolgung entwickelt. Insbesondere werden Jacobimatrizen der Beobachtungsfunktion hergeleitet. Sie werden in der Arbeit so dargestellt, dass sie direkt in einer Programmiersprache implementiert werden können. Im Zuge dieser Arbeit wurde ein Zielverfolgungs-Experiment mit dem Experimentalsystem PAMIR des Fraunhofer FHR durchgeführt. In dem Experiment wurden neben einer Vielzahl von Gelegenheitszielen zwei mit GPS-Geräten ausgerüstete Fahrzeuge von dem Radar beobachtet. Auf Basis dieses Experiments und des Referenzalgorithmus werden Zielverfolgungsergebnisse vorgestellt. Darüber hinaus erweitert diese Arbeit den Referenzalgorithmus um einen Parameter, der die Varianz der Richtungsschätzung des Zielsignals charakterisiert. Dieser Parameter wird adaptiv anhand der geschätzten Signalstärke und der Stärke störender Bodenrückstreuungen festgelegt. Der wesentliche Beitrag dieser Arbeit in Bezug auf diese Erweiterung ist eine gründliche experimentelle Validierung. Erstens zeigt der Vergleich von GPS- und Radar-basierten Richtungsschätzungen, dass dieser Parameter die Verteilung des Messfehlers exzellent beschreibt. Zweitens werden Zielverfolgungsergebnisse mit den GPS-Spuren verglichen. Es zeigt sich, dass der erweiterte Algorithmus sowohl in Bezug auf die Spurgenauigkeit als auch in Bezug auf die Spurkontinuität die Zielverfolgung verbessert