GNSS-based Position and Baseline Determination and Simultaneous Clock Synchronization for Multistatic Synthetic Aperture Radar Constellations

Multistatic constellations can offer various advantages for SAR remote sensing. These concepts are challenging to implement for a series of technical difficulties. The lack of synchronization, caused by the operation of transmitter and receiver with different master clocks, poses one of the fundamental operational problems, contaminating the phase signatures of the radar imaging and challenging its differential ranging accuracy. In addition, baseline accuracy of a few milimeters must achieved, preferrably using data obtained from low-cost GNSS receivers. In this work, we evaluate a synchronization method based on GNSS navigation data and Precise Orbit Determination. The method consists in using in each satellite the same oscillator for the master clock of the GNSS receiver and of the SAR payload, so that the relative time estimation obtained in the precise orbit determination can be used to synchronize the radar data in the post-processing. The simulations suggest the proposed approach is capable of delivering reliable estimates of phase errors in the absence of strong baseline velocity deviations and if multipath and other systematic errors are successfully suppressed or calibrated. In addition, different configurations are evaluate in an attempt to improve the individual baselines estimates by combining GNSS data from several satellites flying in close formation. The preliminary studies indicate that the individual baseline can potentially be improved by using intersatellite links and by implementing a consistency check by comparing the height biases between DEMs generated from different pairs of satellite

Improvement of detection and tracking techniques in multistatic passive radar systems. (Mejora de técnicas de detección y seguimiento en sistemas radar pasivos multiestáticos)

Esta tesis doctoral es el resultado de una intensa actividad investigadora centrada en los sensores radar pasivos para la mejora de las capacidades de detección y seguimiento en escenarios complejos con blancos terrestres y pequeños drones. El trabajo de investigación se ha llevado a cabo en el grupo de investigación coordinado por la Dra. María Pilar Jarabo Amores, dentro del marco diferentes proyectos: IDEPAR (“Improved DEtection techniques for PAssive Radars”), MASTERSAT (“MultichAnnel paSsive radar receiver exploiting TERrestrial and SATellite Illuminators”) y KRIPTON (“A Knowledge based appRoach to passIve radar detection using wideband sPace adapTive prOcessiNg”) financiados por el Ministerio de Economía y Competitividad de España; MAPIS (Multichannel passive ISAR imaging for military applications) y JAMPAR (“JAMmer-based PAssive Radar”), financiados por la Agencia Europea de Defensa (EDA) . El objetivo principal es la mejora de las técnicas de detección y seguimiento en radares pasivos con configuraciones biestáticas y multiestaticas. En el documento se desarrollan algoritmos para el aprovechamiento de señales procedentes de distintos iluminadores de oportunidad (transmisores DVB-T, satélites DVB-S y señales GPS). Las soluciones propuestas han sido integradas en el demostrador tecnológico IDEPAR, desarrollado y actualizado bajo los proyectos mencionados, y validadas en escenarios reales declarados de interés por potenciales usuarios finales (Direccion general de armamento y material, instituto nacional de tecnología aeroespacial y la armada española). Para el desarrollo y evaluación de cadenas de las cadenas de procesado, se plantean dos casos de estudio: blancos terrestres en escenarios semiurbanos edificios y pequeños blancos aéreos en escenarios rurales y costeros. Las principales contribuciones se pueden resumir en los siguientes puntos: • Diseño de técnicas de seguimiento 2D en el espacio de trabajo rango biestático-frecuencia Doppler: se desarrollan técnicas de seguimiento para los dos casos de estudio, localización de blancos terrestres y pequeños drones. Para es último se implementan técnicas capaces de seguir tanto el movimiento del dron como su firma Doppler, lo que permite implementar técnicas de clasificación de blancos. • Diseño de técnicas de seguimiento de blancos capaces de integrar información en el espacio 3D (rango, Doppler y acimut): se diseñan técnicas basadas en procesado en dos etapas, una primera con seguimiento en 2D para el filtrado de falsas alarmas y la segunda para el seguimiento en 3D y la conversión de coordenadas a un plano local cartesiano. Se comparan soluciones basadas en filtros de Kalman para sistemas tanto lineales como no lineales. • Diseño de cadenas de procesado para sistemas multiestáticos: la información estimada del blanco sobre múltiples geometrías biestáticas es utilizada para incremento de las capacidades de localización del blanco en el plano cartesiano local. Se presentan soluciones basadas en filtros de Kalman para sistemas no lineales explotando diferentes medidas biestáticas en el proceso de transformación de coordenadas, analizando las mejoras de precisión en la localización del blanco. • Diseño de etapas de procesado para radares pasivos basados en señales satelitales de las constelaciones GPS DVB-S. Se estudian las características de las señales satelitales identificando sus inconvenientes y proponiendo cadenas de procesado que permitan su utilización para la detección y seguimiento de blancos terrestres. • Estudio del uso de señales DVB-T multicanal con gaps de transmisión entre los diferentes canales en sistemas radares pasivos. Con ello se incrementa la resolución del sistema, y las capacidades de detección, seguimiento y localización. Se estudia el modelo de señal multicanal, sus efectos sobre el procesado coherente y se proponen cadenas de procesado para paliar los efectos adversos de este tipo de señales

Synthetic aperture imagery for high-resolution imaging sonar

Synthetic aperture sonar (SAS) can provide high-resolution underwater images. Traditional fast imaging algorithms designed for multi-receiver synthetic aperture sonar (MSAS) are complex because the point target reference spectrum (PTRS) deduction and imaging algorithm development are complicated. This paper proposes an imaging algorithm for the MSAS system to solve this issue. The proposed method first approximates the two-round slant range based on the phase center approximation method. The PTRS, including the quasi-monostatic and bistatic deformation terms, can be easily deduced. After compensating for the bistatic deformation term based on the interpolation and complex multiplication with the preprocessing step, the MSAS imagery can be simplified to the focus of the traditional monostatic SAS. Therefore, the conventional imaging algorithms designed for traditional monostatic SAS can be used directly. The proposed method providing high-resolution imaging results is more efficient than the traditional methods

Generalized continuous wave synthetic aperture radar for high resolution and wide swath remote sensing

© 2018 IEEE. A generalized continuous wave synthetic aperture radar (GCW-SAR) concept is proposed in this paper. By using full-duplex radio frontend and continuous wave signaling, the GCW-SAR system can overcome a number of limitations inherent within the existing SAR systems and achieve high-resolution and wide-swath remote sensing with low-power signal transmission. Unlike the conventional pulsed SAR and the frequency-modulated continuous-wave SAR, the GCW-SAR reconstructs a radar image by directly correlating the received 1-D raw data after self-interference cancellation with predetermined location-dependent reference signals. A fast imaging algorithm, called the piecewise constant Doppler (PCD) algorithm, is also proposed, which produces the radar image recursively in the azimuth direction without any intermediate step, such as range compression and migration compensation, as required by conventional algorithms. By removing the stop-and-go assumption or slow-time sampling in azimuth, the PCD algorithm not only achieves better imaging quality but also allows for more flexible waveform and system designs. Analyses and simulations show that the GCW-SAR tolerates significant self-interference and works well with a large selection of various system parameters. The work presented in this paper establishes a solid theoretical foundation for next-generation imaging radars

SAR Imagery in Non-Cartesian Geometries

ABSTRACT The subject of the reported work is the improvement of geometrical models for a SAR scanning in Pushbroom, Spotlight, Scansar or Bistatic imaging modes. These researches have been motivated by the planetary cornerstone mission of ESA's long term programme for European Space Science ("Rendez-vous" with a comet, and Fly-Bys of asteroids). In this specific context, the synthetic aperture radar is destined for an important role, but the rules and standard backgrounds of the cartesian geometry are no longer justified. Several new techniques are proposed to handle with an optimal precision the data relative to celestial bodies with a complex geometry (coherent and non-coherent imagery). On the basis of a mathematical rigour (singleness of solutions, convergence of processes, biunivocity of transformations and generalizations), a lot of scenarios are discussed with key relations established (plane and spherical models, bodies with a symetry of revolution and general bodies, specific sensor(s) trajectories as Fly-Bys or flight into orbit with the possibility of an approaching probe). The four methods developed are the tomographic analogy of radar principles (only known, previously, in the usual case of a straight line flight at constant altitude over a plane surface) and Hilbertian techniques for a direct adaptation to the scanned surface geometry, an automated autofocusing which enhances the contrast resulting from a cartesian reconstruction and the coordinates transformation where the real space is converted into a fictitious space where cartesian algorithms are fully rigorous. Beyond the fact that an interpolation step is often unavoidable, the major conclusion of the research is that all the prospected techniques are complementary and that the choice between the methods has to be made according to geometry, objectives and time requirements (reconstruction on board or not). In particular, coordinates transformation techniques are worthy of commendation in case of plane (wavefront curvature balancing) or spherical models in a monostatic situation. Autofocusing methods (judicious ponderation between the usual reconstruction and a reconstruction of the derivative of the key expression of the mathematical formalism with regard to one of its parameters) has proved its validity in an hilly regions of the East of Belgium with low differences in contrast, while the Hilbertian principles are general methods without any restriction on the paths of the probes, the geometry of the celestial body, the modulation scheme and antennae radiation pattern. On the other hand, the tomographic analogy can be applied in all situations where a correct model of the body relief is available, but there are some approximations in the formalism (no antenna pattern modelling, no balancing of the Range Migration)

Impairments in ground moving target indicator (GMTI) radar

Radars on multiple distributed airborne or ground based moving platforms are of increasing interest, since they can be deployed in close proximity to the event under investigation and thus offer remarkable sensing opportunities. Ground moving target indicator (GMTI) detects and localizes moving targets in the presence of ground clutter and other interference sources. Space-time adaptive processing (STAP) implemented with antenna arrays has been a classical approach to clutter cancellation in airborne radar. One of the challenges with STAP is that the minimum detectable velocity (MDV) of targets is a function of the baseline of the antenna array: the larger the baseline (i.e., the narrower the beam), the lower the MDV. Unfortunately, increasing the baseline of a uniform linear array (ULA) entails a commensurate increase in the number of elements. An alternative approach to increasing the resolution of a radar, is to use a large, but sparse, random array. The proliferation of relatively inexpensive autonomous sensing vehicles, such as unmanned airborne systems, raises the question whether is it possible to carry out GMTI by distributed airborne platforms. A major obstacle to implementing distributed GMTI is the synchronization of autonomous moving sensors. For range processing, GMTI processing relies on synchronized sampling of the signals received at the array, while STAP processing requires time, frequency and phase synchronization for beamforming and interference cancellation. Distributed sensors have independent oscillators, which are naturally not synchronized and are each subject to different stochastic phase drift. Each sensor has its own local oscillator, unlike a traditional array in which all sensors are connected to the same local oscillator. Even when tuned to the same frequency, phase errors between the sensors will develop over time, due to phase instabilities. These phase errors affect a distributed STAP system. In this dissertation, a distributed STAP application in which sensors are moving autonomously is envisioned. The problems of tracking, detection for our proposed architecture are of important. The first part focuses on developing a direct tracking approach to multiple targets by distributed radar sensors. A challenging scenario of a distributed multi-input multi-output (MIMO) radar system (as shown above), in which relatively simple moving sensors send observations to a fusion center where most of the baseband processing is performed, is presented. The sensors are assumed to maintain time synchronization, but are not phase synchronized. The conventional approach to localization by distributed sensors is to estimate intermediate parameters from the received signals, for example time delay or the angle of arrival. Subsequently, these parameters are used to deduce the location and velocity of the target(s). These classical localization techniques are referred to as indirect localization. Recently, new techniques have been developed capable of estimating target location directly from signal measurements, without an intermediate estimation step. The objective is to develop a direct tracking algorithm for multiple moving targets. It is aimed to develop a direct tracking algorithm of targets state parameters using widely distributed moving sensors for multiple moving targets. Potential candidate for the tracker include Extended Kalman Filter. In the second part of the dissertation,the effect of phase noise on space-time adaptive processing in general, and spatial processing in particular is studied. A power law model is assumed for the phase noise. It is shown that a composite model with several terms is required to properly model the phase noise. It is further shown that the phase noise has almost linear trajectories. The effect of phase noise on spatial processing is analyzed. Simulation results illustrate the effect of phase noise on degrading the performance in terms of beam pattern and receiver operating characteristics. A STAP application, in which spatial processing is performed (together with Doppler processing) over a coherent processing interval, is envisioned

3D Localization and Tracking Methods for Multi-Platform Radar Networks

Multi-platform radar networks (MPRNs) are an emerging sensing technology due to their ability to provide improved surveillance capabilities over plain monostatic and bistatic systems. The design of advanced detection, localization, and tracking algorithms for efficient fusion of information obtained through multiple receivers has attracted much attention. However, considerable challenges remain. This article provides an overview on recent unconstrained and constrained localization techniques as well as multitarget tracking (MTT) algorithms tailored to MPRNs. In particular, two data-processing methods are illustrated and explored in detail, one aimed at accomplishing localization tasks the other tracking functions. As to the former, assuming a MPRN with one transmitter and multiple receivers, the angular and range constrained estimator (ARCE) algorithm capitalizes on the knowledge of the transmitter antenna beamwidth. As to the latter, the scalable sum-product algorithm (SPA) based MTT technique is presented. Additionally, a solution to combine ARCE and SPA-based MTT is investigated in order to boost the accuracy of the overall surveillance system. Simulated experiments show the benefit of the combined algorithm in comparison with the conventional baseline SPA-based MTT and the stand-alone ARCE localization, in a 3D sensing scenario