Space-Time Adaptive Processing (STAP) has been widely used in spaceborne and airborne radar platforms in order to track ground moving targets. Jammer is an hostile electronic countermeasure that is being used to degrade radar detection and tracking performance. STAP adapts radar&rsquo / s antenna radiating pattern in order to reduce jamming effectiveness. Jamming power that enters the system is decreased with respect to the adapted radiation pattern. In this thesis, a generic STAP radar model is developed and implemented in simulation environment. The implemented radar model demonstrates that, STAP can be used in order to suppress wideband jammer effectiveness together with ground clutter effects.

Space-time Adaptive Processing (STAP) is a two-dimensional filtering technique for antenna array with multiple spatial channels. The name "space-time" describes the coupling of these spatial channels with pulse-Doppler waveforms. Applications for STAP includes ground moving target indicator (GMTI) for airborne radar systems. Today, there are strong interests to develop STAP algorithms for operations in “sample starved” environments, where intense environmental interference can reduce STAP capacity to detect and track ground targets. Careful applications of STAP can effectively overcome these conditions by suppressing these interferences and maximize the signal to interference plus noise ratio (SINR). The Multi-stage Wiener filter (MWF) and principal component signal dependent (PC-SD) algorithm are two such methods that can suppress these interference through truncation of the signal subspace. This thesis makes contribution in several ways. First it details the importance of rank compression and sample compression for effective STAP operations in “sample starved” environments. Second, it shows how MWF and PC-SD could operate in this type of environment. Third it details how a “soft stop” technique like diagonal loading (DL) could improve STAP performance in target detection for MWF and PC-SD. Fourth, this thesis contrasts the performance of several existing “hard stop” techniques in rank compression and introduces a new one using a-priori knowledge.

Under a number of practical operating scenarios, traditional moving target indicator (MTI) systems inadequately suppress ground clutter in airborne radar systems. Due to the moving platform, the clutter gains a nonzero relative velocity and spreads the power across Doppler frequencies. This obfuscates slow-moving targets of interest near the "direct current" component of the spectrum. In response, space-time adaptive processing (STAP) techniques have been developed that simultaneously operate in the space and time dimensions for effective clutter cancellation. STAP algorithms commonly operate under the assumption of homogeneous clutter, where the returns are described by complex, white Gaussian distributions. Empirical evidence shows that this assumption is invalid for many radar systems of interest, including high-resolution radar and radars operating at low grazing angles. We are interested in these heterogeneous cases, i.e., cases when the Gaussian model no longer suffices. Hence, the development of reliable STAP algorithms for real systems depends on the accuracy of the heterogeneous clutter models. The clutter of interest in this work includes heterogeneous texture clutter and point clutter. We have developed a cell-based clutter model (CCM) that provides simple, yet faithful means to simulate clutter scenarios for algorithm testing. The scene generated by the CMM can be tuned with two parameters, essentially describing the spikiness of the clutter scene. In one extreme, the texture resembles point clutter, generating strong returns from localized range-azimuth bins. On the other hand, our model can also simulate a flat, homogeneous environment. We prove the importance of model-based STAP techniques, namely knowledge-aided parametric covariance estimation (KAPE), in filtering a gamut of heterogeneous texture scenes. We demonstrate that the efficacy of KAPE does not diminish in the presence of typical spiky clutter. Computational complexities and susceptibility to modeling errors prohibit the use of KAPE in real systems. The computational complexity is a major concern, as the standard KAPE algorithm requires the inversion of an MNxMN matrix for each range bin, where M and N are the number of array elements and the number of pulses of the radar system, respectively. We developed a Gram Schmidt (GS) KAPE method that circumvents the need of a direct inversion and reduces the number of required power estimates. Another unavoidable concern is the performance degradations arising from uncalibrated array errors. This problem is exacerbated in KAPE, as it is a model-based technique; mismatched element amplitudes and phase errors amount to a modeling mismatch. We have developed the power-ridge aligning (PRA) calibration technique, a novel iterative gradient descent algorithm that outperforms current methods. We demonstrate the vast improvements attained using a combination of GS KAPE and PRA over the standard KAPE algorithm under various clutter scenarios in the presence of array errors.

Le Synthetic Aperture Radar (SAR) aéroporté permet d’obtenir des images hautes résolutions, en compensant un déphasage lié au déplacement de l’avion. Il n’est cependant pas adapté à l’imagerie des cibles mobiles, celles-ci introduisant un déphasage supplémentaire, dépendant de leur vitesse et de leur accélération. En utilisant un système SAR multivoies, il est cependant possible de réaliser des traitements adaptés aux cibles mobiles, dont les principes sont proches du Space-Time Adaptive Processing (STAP). Le Synthetic Aperture Radar (SAR) aéroporté permet d’obtenir des images hautes résolutions, en compensant un déphasage lié au déplacement de l’avion. Il n’est cependant pas adapté à l’imagerie des cibles mobiles, celles-ci introduisant un déphasage supplémentaire, dépendant de leur vitesse et de leur accélération. En utilisant un système SAR multivoies, il est cependant possible de réaliser des traitements adaptés aux cibles mobiles, dont les principes sont proches du Space-Time Adaptive Processing (STAP). / Airborne Synthetic Aperture Radar (SAR) provides high-resolution images, by compensating a phase shift linked to the platform movement. However, this processing is not suited for imaging moving target, for they introduce an additional phase shift, depending on their velocity and acceleration. By using a multichannel SAR system, it is possible to correctly process moving targets. Such a processing is closely related to Space-Time Adaptive Processing (STAP) principles. Airborne Synthetic Aperture Radar (SAR) provides high-resolution images, by compensating a phase shift linked to the platform movement. However, this processing is not suited for imaging moving target, for they introduce an additional phase shift, depending on their velocity and acceleration. By using a multichannel SAR system, it is possible to correctly process moving targets. Such a processing is closely related to Space-Time Adaptive Processing (STAP) principles.

Le concept de radar passif aéroporté repose sur l’utilisation de plusieurs antennes réseau, disposées sur une plateforme en vue de couvrir un angle solide large de détection, en s’appuyant sur l’utilisation de signaux d’opportunité provenant d’émetteurs au sol. La détection aéroportée à partir de signaux d’opportunité est intéressante, notamment pour assurer l’autoprotection d’un avion ou d’un hélicoptère ; en revanche elle constitue un défi technique notamment en raison du niveau des signaux interférents, en provenance de l’émetteur et des trajets multiples indirects (le fouillis), bien supérieur au niveau de signal utile diffusé par la cible à détecter. D’autres effets, tels que la structure arbitraire des signaux (forme d’onde non-radar) et sa conséquence sur les lobes secondaires en distance, contribuent à la complexité du traitement à mettre en œuvre.Le point de départ des recherches se situe à l’intersection des techniques de radar passif (utilisant la corrélation entre un signal de référence non connu a priori et les signaux diffus renvoyés par l’environnement) et les techniques de type STAP (Space Time Adaptive Processing) utilisées pour la détection des cibles mobiles par les radars aéroportés conventionnels. Dans ce contexte, les travaux de thèse permettent d’étendre d’une part la caractérisation et la qualification des signaux « radar passif » à une configuration aéroportée, d’autre part les techniques STAP à une configuration bistatique et à des signaux de forme arbitraire et non structurés comme des signaux radar. Les recherches mettent en évidence l’importance primordiale du trajet direct et des premiers échos de fouillis qui parasitent la caractérisation spatio-temporelle des échos reçus dans la case distance de la cible sous test. La caractéristique du fouillis, habituellement tracée dans le plan Doppler-angle, se trouve affectée par ces interférences qu’il faut éliminer au préalable. Pour cela, un premier filtre à réponse finie est mis en œuvre sur chaque capteur, puis le traitement STAP est appliqué à l’ensemble du réseau d’antennes.Les traitements proposés sont simulés et les performances en détection sont analysées. Une expérimentation est conduite, à l’aide d’un réseau de 4 antennes mobiles au sol. Les conditions sont réunies pour collecter des signaux de fouillis étalés en Doppler et analyser l’effet d’une forme d’onde non-radar. Les traitements d’élimination des interférences sont mis en œuvre et ainsi qualifiés expérimentalement. / The novel concept for the airborne passive radar is to have multiple passive receiving arrays covering a 4 steradian angle around the platform which makes use of the ground-based stationary transmitter as the illuminator of opportunity. This challenging passive radar configuration would well find application for localized covert surveillance on an airborne platform such as an unmanned aerial vehicle, helicopter, etc. For the airborne passive radar, during moving target detections, it encounters the effects of strong interfering signal returns against the weak target returns where this severe interfering environment is usually characterized by the high levels of direct path and clutter against the thermal noise background. Due to the continuous wave, random and aperiodic nature of the passive signal and given the strong direct path and clutter signals, their random range sidelobes couplings into further range cells will seriously exacerbate the background interference, making target detections a big challenge. Moreover, owing to the platform motion, the clutter received by the airborne passive radar is not only extended in both range and angle, it is also spread over a region in Doppler frequency which further complicates the problem.This research work is focused on identifying and analyzing the critical issues faced by the airborne passive radar on moving target detections and to develop effective signal processing schemes for improved performance. As a first step, it is important to accurately derive the model for the received passive signals and consequently, efficient signal processing schemes can be studied to mitigate and to improve detections performance. The signal processing schemes for the airborne passive radar can be segregated into a two-step interference cancellation process where the direct path and strong clutter coupling components (and their corresponding random range sidelobes) present in the received signal at each antenna element can first be effectively suppressed by the adaptive interference cancellation algorithm prior to matched filter processing. Further cancellation on the residual random range sidelobes couplings and on the spatial-Doppler dependent clutter can be achieved using reduced-dimension STAP. Trials based on the ground-based moving passive radar experiments are conducted as the final part of this research work to validate and evaluate the signal processing schemes which is a major progress towards implementing an operational airborne passive radar.

En environnements hostiles, les signaux GNSS (Global Navigation Satellite System)peuvent être soumis à des risques de brouillages intentionnels. Basées sur un réseau d'antennes adaptatif, les solutions spatio-temporelles (STAP) ont déjà montré de bonnes performances de réjection des interférences. Toutefois, lorsque le module GNSS est placé sous les pales d'un hélicoptère, des effets non-stationnaires, appelés Rotor Blade Modulation (RBM), créés par les multiples réflexions du signal sur les pales du rotor, peuvent dégrader les techniques usuelles d’antibrouillage. Le signal utile GNSS n’est alors plus accessible. Le travail de la thèse consiste donc à élaborer un système de protection des signaux GNSS adapté à la RBM. Pour cela, un modèle innovant de multitrajets, adapté à ce type de phénomène, a été développé. La comparaison de simulations électromagnétiques représentatives et de mesures expérimentales sur hélicoptère EC-120 a permis de valider ce modèle. Celui-ci permet d'estimer, par maximum de vraisemblance, les paramètres de la contribution non-stationnaire du signal reçu. Enfin, l'association d'un algorithme de filtrage des multitrajets par projection oblique et d'un traitement STAP permet d'éliminer la contribution dynamique puis statique de l'interférence. Les simulations montrent que le signal utile GNSS est alors de nouveau exploitable. / In hostile environments, Global Navigation Satellite System (GNSS) can be disturbed by intentional jamming. Using antenna arrays, space-time adaptive algorithm (STAP) isone of the most efficient methods to deal with these threats. However, when a GNSS receiver is placed near rotating bodies, non-stationary effects called Rotor Blade Modulation (RBM) are created by the multipaths on the blades of the helicopter. They can degrade significantly the anti-jamming system and the signal of interest could belost. The work of the thesis is, consequently, to develop a GNSS protection system adapted to the RBM. In this way, an innovative multipath model, adapted to this phenomenon, has been developed. The model is then confirmed by comparison with a symptotic electromagnetic simulations and experiments conducted on an EC-120helicopter. Using a Maximum Likelihood algorithm, the parameters of the non-stationary part of the received signal have been estimated. And finally, the RBM anti-jamming solution, combining oblique projection algorithm and academic STAP, can mitigate dynamic and static contributions of interferences. In the end, the navigation information is available again.

[pt] Processamento em arranjos de sensores é uma área com vasta aplicação, tanto civil quanto militar, por exemplo em sonar, radar, sismologia e comunicações sem fio. Por meio de processamento espacial e espácio-temporal é possível melhorar suas funcionalidades e explorar novas possibilidades. Esta área vem atraindo cada vez mais a atenção e os esfor¸cos da comunidade científica, especialmente agora, em que antenas phased-array se estabeleceram como uma tecnologia comercial e madura. Neste contexto, nós tratamos o problema de processamento com posto reduzido em processamento espacial (beamforming) e espácio-temporal de sinais radar e a nova área de radares com função dual de radar e comunicações (dualfunction radar-communications, DFRC), que pode ser resumida na incorporação de mensagens de comunicações nas transmissıes radar como uma tarefa secundária. Nesta tese, nós investigamos a aplicação de um novo esquema de reduções de posto baseado em interpolação e decimação em duas áreas distintas: processamento espacial e processamento espácio-temporal de sinais radar. Este algoritmo para redução de posto nunca havia sido testado nestes ambientes antes e apresentou resultados bastante expressivos. Nós também propomos simplificações para reduzir a complexidade computacional do algoritmo em bemforming. Quanto ao tópico de DFRC, nós propomos dois métodos originais para incorporar modulação de amplitude/fase aos lóbulos laterais do diagrama de irradiação do radar de forma robusta. Os métodos propostos são muito mais simples do que o estado-da-arte e apresentam desempenho superior em termos de robustez e aplicabilidade em operações de tempo-real. Nós ainda provemos várias outras análises, comparações e contribuições a esta nova área. / [en] Array processing is an area with many civilian and military applications, e.g. sonar, radar, seismology and wireless communications. By means of space and space-time processing it is possible to enhance their features and explore new possibilities. This area has been attracting increasingly more attention and gathering more efforts of the science community, especially now, that phased array antennas are established as a commercial and mature technology. Within this context, we address the problem of reduced rank processing in space and space-time radar signal processing and the new area of dual-function radar-communications (DFRC), which may be summarized as embedding communication messages into radar emissions as a secondary task for the radar. In this thesis, we investigate the application of a new joint interpolation and decimation rank reducing scheme in two different areas: beamforming and space-time radar processing. This rank reducing algorithm was never tested within these contexts before and shows impressive results. We also propose simplifications for decreasing the computational complexity of the algorithm in beamforming. In the topic of DFRC, we propose two original robust radar-embedded sidelobe phase/amplitude modulation methods which have simple closed form equations. The proposed methods are much simpler than the state of the art and have superior performance in terms of robustness and real-time applicability.