230 research outputs found
Interference Mitigation Effects on Synthetic Aperture Radar Coherent Data Products
Both radio frequency interference from sources external to the synthetic aperture radar system and techniques to mitigate radio frequency interference can degrade the quality of the image products. Often it is the second order data products derived from the images that are of the most value for a synthetic aperture radar system. Preserving the quality of these data products, in the presence of radio frequency interference, is paramount to maintaining the utility of the sensor.This dissertation examines the effects of interference mitigation upon coherent data products of fine-resolution, high frequency synthetic aperture radars using stretch processing. Novel interference mitigation techniques are introduced that operate on single or multiple apertures of data that increase average coherence compared to existing techniques. A novel contrast metric is combined with existing image quality and average coherence metrics to compare multiple mitigation techniques. The characteristics of interference mitigation techniques that restore coherence are revealed.Electrical Engineerin
Adaptive waveform design for SAR in a crowded spectrum
This thesis concerns the development of an adaptive waveform design scheme for synthetic
aperture radar (SAR) to support its operation in the increasingly crowded radio
frequency (RF) spectrum, focusing on mitigating the effects of external RF interference.
The RF spectrum is a finite resource and the rapid expansion of the telecommunications
industry has seen radar users face a significant restriction in the range of available
operational frequencies. This crowded spectrum scenario leads to increased likelihood
of RF interference either due to energy leakage from neighbouring spectral users or
from unlicensed transmitters.
SAR is a wide bandwidth radar imaging mode which exploits the motion of the radar
platform to form an image using multiple one dimensional profiles of the scene of interest
known as the range profile. Due to its wideband nature, SAR is particularly vulnerable
to RF interference which causes image impairments and overall reduction in quality.
Altering the approach for radar energy transmission across the RF spectrum is now
imperative to continue effective operation.
Adaptive waveforms have recently become feasible for implementation and offer the
much needed flexibility in the choice and control over radar transmission. However,
there is a critically small processing time frame between waveform reception and transmission,
which necessitates the use of computationally efficient processing algorithms
to use adaptivity effectively.
This simulation-based study provides a first look at adaptive waveform design for SAR
to mitigate the detrimental effects of RF interference on a pulse-to-pulse basis. Standard
SAR systems rely on a fixed waveform processing format on reception which restricts its
potential to reap the benefits of adaptive waveform design. Firstly, to support waveform
design for SAR, system identification techniques are applied to construct an alternative
receive processing method which allows flexibility in waveform type. This leads to the
main contribution of the thesis which is the formation of an adaptive spectral waveform
design scheme. A computationally efficient closed-form expression for the waveform spectrum that minimizes the error in the estimate of the SAR range profile on a pulse to pulse basis is
derived. The range profile and the spectrum of the interference are estimated at each
pulse. The interference estimate is then used to redesign the proceeding waveform for
estimation of the range profile at the next radar platform position. The solution necessitates
that the energy is spread across the spectrum such that it competes with the
interferer. The scenario where the waveform admits gaps in the spectrum in order to
mitigate the effects of the interference is also detailed and is the secondary major thesis
contribution. A series of test SAR images demonstrate the efficacy of these techniques
and yield reduced interference effects compared to the standard SAR waveform
Radiometric Degradation Associated with Terrain Height Variations and Pulse Duration in Scan-On-Receive SAR Images
Scan-on-receive (SCORE) is a key digital beamforming (DBF) technique for future high-resolution wide-swath spaceborne synthetic aperture radar (SAR) systems. Compared to a conventional approach, it allows to improve the signal-to-noise ratio and the range ambiguity suppression. Nevertheless, it also exposes the system to new errors, associated with terrain height variations and pulse duration. This work investigates the mutual effect of these error sources on the SCORE SAR image. A novel, closed, mathematical expression is derived, respectively, for the impulse response function of the image formation process and for the radiometric loss affecting the image pixels. This makes it possible to predict and quantify the effect of terrain height variations and pulse duration as a function of system, processing, and geometric parameters. The numerical results, based on the end-to-end simulation of the SAR image formation process in different operational scenarios, highlight the relevance of this effect and of the derived analytical description, especially in view of the demanding radiometric quality requirements imposed on future SAR images
Phase History Decomposition for Efficient Scatterer Classification in SAR Imagery
A new theory and algorithm for scatterer classification in SAR imagery is presented. The automated classification process is operationally efficient compared to existing image segmentation methods requiring human supervision. The algorithm reconstructs coarse resolution subimages from subdomains of the SAR phase history. It analyzes local peaks in the subimages to determine locations and geometric shapes of scatterers in the scene. Scatterer locations are indicated by the presence of a stable peak in all subimages for a given subaperture, while scatterer shapes are indicated by changes in pixel intensity. A new multi-peak model is developed from physical models of electromagnetic scattering to predict how pixel intensities behave for different scatterer shapes. The algorithm uses a least squares classifier to match observed pixel behavior to the model. Classification accuracy improves with increasing fractional bandwidth and is subject to the high-frequency and wide-aperture approximations of the multi-peak model. For superior computational efficiency, an integrated fast SAR imaging technique is developed to combine the coarse resolution subimages into a final SAR image having fine resolution. Finally, classification results are overlaid on the SAR image so that analysts can deduce the significance of the scatterer shape information within the image context
Compressive Sensing and Its Applications in Automotive Radar Systems
Die Entwicklung in Richtung zu autonomem Fahren verspricht, kĂŒnftig einen sicheren
Verkehr ohne tödliche UnfÀlle zu ermöglichen, indem menschliche Fahrer vollstÀndig
ersetzt werden. Dadurch entfÀllt der Faktor des menschlichen Fehlers, der aus
MĂŒdigkeit, Unachtsamkeit oder Alkoholeinfluss resultiert. Um jedoch eine breite
Akzeptanz fĂŒr autonome Fahrzeuge zu erreichen und es somit eines Tages vollstĂ€ndig
umzusetzen, sind noch eine Vielzahl von Herausforderungen zu lösen. Da in einem
autonomen Fahrzeug kein menschlicher Fahrer mehr in NotfÀllen eingreifen kann,
mĂŒssen sich autonome Fahrzeuge auf leistungsfĂ€hige und robuste Sensorsysteme
verlassen können, um in kritischen Situationen auch unter widrigen Bedingungen
angemessen reagieren zu können. Daher ist die Entwicklung von Sensorsystemen
erforderlich, die fĂŒr FunktionalitĂ€ten jenseits der aktuellen advanced driver assistance
systems eingesetzt werden können. Dies resultiert in neuen Anforderungen, die erfĂŒllt
werden mĂŒssen, um sichere und zuverlĂ€ssige autonome Fahrzeuge zu realisieren, die
weder Fahrzeuginsassen noch Passanten gefÀhrden. Radarsysteme gehören zu den
SchlĂŒsselkomponenten unter der Vielzahl der verfĂŒgbaren Sensorsysteme, da sie im
Gegensatz zu visuellen Sensoren von widrigen Wetter- und Umgebungsbedingungen
kaum beeintrĂ€chtigt werden. DarĂŒber hinaus liefern Radarsysteme zusĂ€tzliche
Umgebungsinformationen wie Abstand, Winkel und relative Geschwindigkeit zwischen
Sensor und reflektierenden Zielen. Die vorliegende Dissertation deckt im Wesentlichen
zwei Hauptaspekte der Forschung und Entwicklung auf dem Gebiet der Radarsysteme
im Automobilbereich ab. Ein Aspekt ist die Steigerung der Effizienz und Robustheit
der Signalerfassung und -verarbeitung fĂŒr die Radarperzeption. Der andere Aspekt ist
die Beschleunigung der Validierung und Verifizierung von automated cyber-physical
systems, die parallel zum Automatisierungsgrad auch eine höhere KomplexitÀt
aufweisen.
Nach der Analyse zahlreicher möglicher Compressive Sensing Methoden, die im
Bereich Fahrzeugradarsysteme angewendet werden können, wird ein rauschmoduliertes
gepulstes Radarsystem vorgestellt, das kommerzielle Fahrzeugradarsysteme in
seiner Robustheit gegenĂŒber Rauschen ĂŒbertrifft. Die Nachteile anderer gepulster
Radarsysteme hinsichtlich des Signalerfassungsaufwands und der Laufzeit werden
durch die Verwendung eines Compressive Sensing-Signalerfassungs- und Rekonstruktionsverfahrens
in Kombination mit einer Rauschmodulation deutlich verringert.
Mit Compressive Sensing konnte der Aufwand fĂŒr die Signalerfassung um 70% reduziert
werden, wĂ€hrend gleichzeitig die Robustheit der Radarwahrnehmung auch fĂŒr signal-to-noise-ratio-Pegel nahe oder unter Null erreicht wird. Mit einem validierten
Radarsensormodell wurde das Rauschradarsystem emuliert und mit einem
kommerziellen Fahrzeugradarsystem verglichen. Datengetriebene Wettermodelle
wurden entwickelt und wÀhrend der Simulation angewendet, um die Radarleistung
unter widrigen Bedingungen zu bewerten. WĂ€hrend eine BesprĂŒhung mit Wasser die
RadomdÀmpfung um 10 dB erhöht und Spritzwasser sogar um 20 dB, ergibt sich die
eigentliche Begrenzung aus der Rauschzahl und Empfindlichkeit des EmpfÀngers. Es
konnte bewiesen werden, dass das vorgeschlagene Compressive Sensing Rauschradarsystem
mit einer zusÀtzlichen SignaldÀmpfung von bis zu 60 dB umgehen kann
und damit eine hohe Robustheit in ungĂŒnstigen Umwelt- und Wetterbedingungen
aufweist.
Neben der Robustheit wird auch die Interferenz berĂŒcksichtigt. Zum einen wird
die erhöhte Störfestigkeit des Störradarsystems nachgewiesen. Auf der anderen
Seite werden die Auswirkungen auf bestehende Fahrzeugradarsysteme bewertet und
Strategien zur Minderung der Auswirkungen vorgestellt.
Die Struktur der Arbeit ist folgende. Nach der EinfĂŒhrung der Grundlagen
und Methoden fĂŒr Fahrzeugradarsysteme werden die Theorie und Metriken hinter
Compressive Sensing gezeigt. DarĂŒber hinaus werden weitere Aspekte wie Umgebungsbedingungen,
unterschiedliche Radararchitekturen und Interferenz erlÀutert.
Der Stand der Technik gibt einen Ăberblick ĂŒber Compressive Sensing-AnsĂ€tze und
Implementierungen mit einem Fokus auf Radar. DarĂŒber hinaus werden Aspekte
von Fahrzeug- und Rauschradarsystemen behandelt. Der Hauptteil beginnt mit
der Vorstellung verschiedener AnsĂ€tze zur Nutzung von Compressive Sensing fĂŒr
Fahrzeugradarsysteme, die in der Lage sind, die Erfassung und Wahrnehmung von
Radarsignalen zu verbessern oder zu erweitern. AnschlieĂend wird der Fokus auf
ein Rauschradarsystem gelegt, das mit Compressive Sensing eine effiziente Signalerfassung
und -rekonstruktion ermöglicht. Es wurde mit verschiedenen Compressive
Sensing-Metriken analysiert und in einer Proof-of-Concept-Simulation bewertet. Mit
einer Emulation des Rauschradarsystems wurde das Potential der Compressive Sensing
Signalerfassung und -verarbeitung in einem realistischeren Szenario demonstriert.
Die Entwicklung und Validierung des zugrunde liegenden Sensormodells wird ebenso
dokumentiert wie die Entwicklung der datengetriebenen Wettermodelle. Nach der
Betrachtung von Interferenz und der Koexistenz des Rauschradars mit kommerziellen
Radarsystemen schlieĂt ein letztes Kapitel mit Schlussfolgerungen und einem
Ausblick die Arbeit ab.Developments towards autonomous driving promise to lead to safer traffic, where fatal
accidents can be avoided after making human drivers obsolete and hence removing
the factor of human error. However, to ensure the acceptance of automated driving
and make it a reality one day, still a huge amount of challenges need to be solved.
With having no human supervisors, automated vehicles have to rely on capable and
robust sensor systems to ensure adequate reactions in critical situations, even during
adverse conditions. Therefore, the development of sensor systems is required that
can be applied for functionalities beyond current advanced driver assistance systems.
New requirements need to be met in order to realize safe and reliable automated
vehicles that do not harm passersby.
Radar systems belong to the key components among the variety of sensor systems.
Other than visual sensors, radar is less vulnerable towards adverse weather and
environment conditions. In addition, radar provides complementary environment
information such as target distance, angular position or relative velocity, too. The
thesis ad hand covers basically two main aspects of research and development in the
field of automotive radar systems. One aspect is to increase efficiency and robustness
in signal acquisition and processing for radar perception. The other aspect is to
accelerate validation and verification of automated cyber-physical systems that
feature more complexity along with the level of automation.
After analyzing a variety of possible Compressive Sensing methods for automotive
radar systems, a noise modulated pulsed radar system is suggested in the thesis at
hand, which outperforms commercial automotive radar systems in its robustness
towards noise. Compared to other pulsed radar systems, their drawbacks regarding
signal acquisition effort and computation run time are resolved by using noise modulation
for implementing a Compressive Sensing signal acquisition and reconstruction
method. Using Compressive Sensing, the effort in signal acquisition was reduced by
70%, while obtaining a radar perception robustness even for signal-to-noise-ratio
levels close to or below zero. With a validated radar sensor model the noise radar
was emulated and compared to a commercial automotive radar system. Data-driven
weather models were developed and applied during simulation to evaluate radar performance
in adverse conditions. While water sprinkles increase radome attenuation
by 10 dB and splash water even by 20 dB, the actual limitation comes from noise
figure and sensitivity of the receiver. The additional signal attenuation that can be
handled by the proposed compressive sensing noise radar system proved to be even up to 60 dB, which ensures a high robustness of the receiver during adverse weather
and environment conditions.
Besides robustness, interference is also considered. On the one hand the increased
robustness towards interference of the noise radar system is demonstrated. On
the other hand, the impact on existing automotive radar systems is evaluated and
strategies to mitigate the impact are presented.
The structure of the thesis is the following. After introducing basic principles
and methods for automotive radar systems, the theory and metrics of Compressive
Sensing is presented. Furthermore some particular aspects are highlighted such as
environmental conditions, different radar architectures and interference. The state of
the art provides an overview on Compressive Sensing approaches and implementations
with focus on radar. In addition, it covers automotive radar and noise radar related
aspects. The main part starts with presenting different approaches on making use
of Compressive Sensing for automotive radar systems, that are capable of either
improving or extending radar signal acquisition and perception. Afterwards the focus
is put on a noise radar system that uses Compressive Sensing for an efficient signal
acquisition and reconstruction. It was analyzed using different Compressive Sensing
metrics and evaluated in a proof-of-concept simulation. With an emulation of the
noise radar system the feasibility of the Compressive Sensing signal acquisition and
processing was demonstrated in a more realistic scenario. The development and
validation of the underlying sensor model is documented as well as the development
of the data-driven weather models. After considering interference and co-existence
with commercial radar systems, a final chapter with conclusions and an outlook
completes the work
Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water
The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques
Radar Technology
In this book âRadar Technologyâ, the chapters are divided into four main topic areas: Topic area 1: âRadar Systemsâ consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: âRadar Applicationsâ shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: âRadar Functional Chain and Signal Processingâ describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: âRadar Subsystems and Componentsâ consists of design technology of radar subsystem components like antenna design or waveform design
Waveform-Diverse Stretch Processing
Stretch processing with the use of a wideband LFM transmit waveform is a commonly used technique, and its popularity is in large part due to the large time-bandwidth product that provides fine range resolution capabilities for applications that require it. It allows pulse compression of echoes at a much lower sampling bandwidth without sacrificing any range resolution. Previously, this technique has been restrictive in terms of waveform diversity because the literature shows that the LFM is the only type of waveform that will result in a tone after stretch processing. However, there are also many examples in the literature that demonstrate an ability to compensate for distortions from an ideal LFM waveform structure caused by various hardware components in the transmitter and receiver. This idea of compensating for variations is borrowed here, and the use of nonlinear FM (NLFM) waveforms is proposed to facilitate more variety in wideband waveforms that are usable with stretch processing. A compensation transform that permits the use of these proposed NLFM waveforms replaces the final fast Fourier transform (FFT) stage of the stretch processing configuration, but the rest of the RF receive chain remains the same. This modification to the receive processing structure makes possible the use of waveform diversity for legacy radar systems that already employ stretch processing. Similarly, using the same concept of compensating for distortions to the LFM structure along with the notion that a Fourier transform is essentially the matched filter bank for an LFM waveform mixed with an LFM reference, a least-squares based mismatched filtering (MMF) scheme is proposed. This MMF could likewise be used to replace thefinal FFT stage, and can also facilitate the application of NLFM waveforms to legacy radar systems. The efficacy of these filtering approaches (compensation transform and least-squares based MMF) are demonstrated in simulation and experimentally using open-air measurements and are applied to different scenarios of NLFM waveform to assess the results and provide a means of comparison between the two techniques
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