This dissertation deals with techniques that enhance the detection of ground targets by airborne radar. The methods employed deal with the problem of air to ground detection by breaking the problem into two broad categories. The first category deals with improving detection of moving targets by using space-time adaptive processing (STAP) in a multistatic configuration. Mult-static STAP provides increased detection performance by observing targets from multiple perspectives. Multiple viewing perspectives afford more opportunities to the combined system for observing radial velocity of the target more directly, thus increasing Doppler that helps distinguish the target from background clutter. Detection performance also improves through an increased number of independent observations of a target, which reduces the likelihood of the target fading for the combined system. Increasing detection performance by increasing the number of independent observations is referred to in communications theory as channel diversity. The second part of this dissertation deals with the problem of distinguishing stationary targets from background clutter within a Synthetic Aperture Radar image. Stationary target discrimination is accomplished by exploiting the statistical nature of multifaceted metallic objects within a scene. The performance improvement for both moving and non-moving improvement methods is characterized and compared to other systems that attempt to accomplish the same end using different means.

The effects of wind farm installation on the conventional monostatic radar operation have been investigated in previous studies. The interference on radar operation is due to the complex scattering characteristics from the wind turbine structure. This research considers alternative approach for studying and potentially mitigating these negative impacts by adapting the multistatic radar system technique. This radar principle is well known and it is attracting research interest recently, but has not been applied in modelling the wind farm interference on multistatic radar detection and tracking of multiple targets. The research proposes two areas of novelties. The first area includes the simulation tool development of multistatic radar operation near a wind farm environment. The second area includes the adaptation of Range-Only target detection approach based on mathematical and/or statistical methods for target detection and tracking, such as Interval Analysis and Particle Filter. These methods have not been applied against such complex detection scenario of large number of targets within a wind farm environment. Range-Only target detection approach is often considered to achieve flexibility in design and reduction in cost and complexity of the radar system. However, this approach may require advanced signal processing techniques to effectively associate measurements from multiple sensors to estimate targets positions. This issue proved to be more challenging for the complex detection environment of a wind farm due to the increase in number of measurements from the complex radar scattering of each turbine. The research conducts a comparison between Interval Analysis and Particle Filter. The comparison is based on the performance of the two methods according to three aspects; number of real targets detected, number of ghost targets detected and the accuracy of the estimated detections. Different detection scenarios are considered for this comparison, such as single target detection, wind farm detection, and ultimately multiple targets at various elevations within a wind farm environment.

Passive localization of aircraft in flight using signal time of arrival (TOA) poses some unique challenges. The sensors must be deployed in an approximately coplanar configuration, which produces significant vertical uncertainty in the estimated position. This dissertation examines the traditional algorithms used in passive localization. It presents general forms of linear TOA, time difference of arrival (TDOA), angle of arrival (AOA), and frequency difference of arrival (FDOA) equations from the literature and explains how to apply an intuitive geometric interpretation of these equations. It presents two novel algorithms for passive localization. One uses a one dimensional AOA (1AOA) to improve the vertical estimate. The other employs an a priori estimate to approximate the non-linear localization problem as a linear problem and produce a high quality position estimate. A comprehensive survey of the literature is presented. This dissertation provides a summary and classification of passive localization algorithms from the literature with simple descriptions of how the form of the equations relate to their numerical stability. It presents two novel algorithms for passive localization. The hybrid multilateration and triangulation algorithm improves wide area multilateration by using vertical 1AOA to constrain the vertical position. The multilateration with a priori estimates algorithm provides a linear localization method that utilizes previous location estimates.

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Ground penetrating radar (GPR) has been extensively utilized as a highly efficient and non-destructive testing method for infrastructure evaluation, such as highway rebar detection, bridge decks inspection, asphalt pavement monitoring, underground pipe leakage detection, railroad ballast assessment, etc. The focus of this dissertation is to investigate the key techniques to tackle with GPR signal processing from three perspectives: (1) Removing or suppressing the radar clutter signal; (2) Detecting the underground target or the region of interest (RoI) in the GPR image; (3) Imaging the underground target to eliminate or alleviate the feature distortion and reconstructing the shape of the target with good fidelity. In the first part of this dissertation, a low-rank and sparse representation based approach is designed to remove the clutter produced by rough ground surface reflection for impulse radar. In the second part, Hilbert Transform and 2-D Renyi entropy based statistical analysis is explored to improve RoI detection efficiency and to reduce the computational cost for more sophisticated data post-processing. In the third part, a back-projection imaging algorithm is designed for both ground-coupled and air-coupled multistatic GPR configurations. Since the refraction phenomenon at the air-ground interface is considered and the spatial offsets between the transceiver antennas are compensated in this algorithm, the data points collected by receiver antennas in time domain can be accurately mapped back to the spatial domain and the targets can be imaged in the scene space under testing. Experimental results validate that the proposed three-stage cascade signal processing methodologies can improve the performance of GPR system.

I takt med att ubåtarna blir allt tystare och svårare att detektera ställs allt högre krav på de sensorer som utvecklas för hålla jämna steg med denna utveckling. Redan under 80-talet kunde man konstatera att ubåtarna hade blivit så tysta att passiv detektering inte räckte till varför intresset istället riktades mot primärt aktiva system. Aktiv sändning medför sina egna nackdelar och tillsammans med de tekniker som utvecklats för att dämpa ekona från en ubåt gör att inte ens en aktiv, monostatisk sonar alltid ger tillfredsställande resultat. Till Försvarsmaktens nya medeltunga helikopter HKP14 har ett nytt sonarsystem införskaffats med möjlighet till fusionerad signalbehandling (s.k. multistatisk sonar) av signaler mottagna från flera olika mottagare såsom t.ex. sonarbojar.   Undersökningen syftar till att belysa vilka fördelar som kan erhållas vid helikopterbaserad, multistatisk ubåtsjakt och visar med ett antal räkneexempel bland annat att en större räckvidd och därmed även ett större detekteringsområde kan förväntas i en multistatisk konfiguration. Beräkningarna är gjorda med utgångspunkt i Uricks sonarekvationer men då faktorer såsom reverberation och kanalutbredning har avgränsats bort är det osäkert hur väl dessa resultat skulle stämma överens med en fältstudie. Utifrån de typfall som har undersökts visar emellertid studien på att de teoretiska fördelarna med ett multistatiskt system är tydliga och att dessa rent logiskt i viss utsträckning även borde gälla i praktiken. / The fact that submarines are becoming more silent and therefore harder to detect has led to an ever-increasing demand for more sensitive and sophisticated sensors to keep up with this development. As early as the 1980s it became obvious that submarines had become so silent that passive detection was not enough and the focus shifted toward active systems instead. Active transmission has its own disadvantages, and new techniques to silence submarines and reduce their acoustic signature even further have led to a situation where not even active, monostatic sonar always produces a satisfactory result. Along with the new medium sized helicopter (NH90), the Swedish Armed Forces have purchased a new sonar system that allows fused signal processing, using signals received by different receivers, such as sonobuoys. The aim of the study is to show what advantages can be gained from helicopter-based multistatic anti-submarine warfare and to show, by a number of arithmetic examples, that greater detection ranges and thus greater detection areas can be expected from a multistatic configuration. The examples are based on Urick’s sonar equations, but since factors such as reverberation and channel propagation of sound have been excluded from the study, it is uncertain how these results would compare to a field study. However, the study clearly shows the theoretical advantages of a multistatic system and that, on the basis of simple logic, these results should be feasible, to some extent, in practice.

Ground penetrating radar (GPR) has been extensively utilized as a highly efficient and non-destructive testing method for infrastructure evaluation, such as highway rebar detection, bridge decks inspection, asphalt pavement monitoring, underground pipe leakage detection, railroad ballast assessment, etc. The focus of this dissertation is to investigate the key techniques to tackle with GPR signal processing from three perspectives: (1) Removing or suppressing the radar clutter signal; (2) Detecting the underground target or the region of interest (RoI) in the GPR image; (3) Imaging the underground target to eliminate or alleviate the feature distortion and reconstructing the shape of the target with good fidelity. In the first part of this dissertation, a low-rank and sparse representation based approach is designed to remove the clutter produced by rough ground surface reflection for impulse radar. In the second part, Hilbert Transform and 2-D Renyi entropy based statistical analysis is explored to improve RoI detection efficiency and to reduce the computational cost for more sophisticated data post-processing. In the third part, a back-projection imaging algorithm is designed for both ground-coupled and air-coupled multistatic GPR configurations. Since the refraction phenomenon at the air-ground interface is considered and the spatial offsets between the transceiver antennas are compensated in this algorithm, the data points collected by receiver antennas in time domain can be accurately mapped back to the spatial domain and the targets can be imaged in the scene space under testing. Experimental results validate that the proposed three-stage cascade signal processing methodologies can improve the performance of GPR system.

This master’s thesis deals with the concept of passive multistatic radar. The radar system exploits WiFi or WiMAX transmitters as the source of radiolocation signal. The transmitters are considered non-cooperative. The master’s thesis evaluates limitations arising from utilization of WiFi or WiMAX signals. A Matlab simulator was created as a part of the thesis, which was used to verify the basic idea behind this concept. Based on the results of real-life simulations, conclusions are suggested towards a possible application of WiFi/WiMAX radar.

Le sujet porte sur l'étude de systèmes SAS (Synthetic Aperture Sonar) multistatiques. Ces systèmes permettent d'obtenir des images de cibles mieux résolues qu'avec un sonar classique à partir d'ondes acoustiques. Le SAS est largement exploité en configuration monostatique mais il existe très peu d'études à ce jour en SAS multistatique. Le travail consiste donc à évaluer les performances en configuration bistatique et multistatique et à les comparer à celles connues en configuration monostatique. Une méthode de calcul utilisée en radar a donc été mise en oeuvre en sonar de façon à expliciter la résolution en configuration bistatique, ce qui est un résultat original de ce travail. L'algorithme classiquement utilisé pour reconstruire des images repose sur l'hypothèse que la cible est une somme de points brillants. Cette hypothèse n'est pas bien adaptée en acoustique sous-marine. Un nouvel algorithme a donc été développé dans le but de se rapprocher des phénomènes de diffraction présents à l'interface entre l'eau et la cible. Le modèle de champ diffracté est obtenu par la combinaison d'équations intégrales de frontière avec l'approximation de Kirchhoff. Une méthode de reconstruction d'images par transformée de Fourier 2D de ce modèle a été implémentée et testée sur des données simulées, puis sur des données obtenues lors d'essais en cuve. Le nouvel algorithme montre une meilleure précision de la reconstruction et la capacité de pouvoir extraire de l'information quantitative de la cible. L'intérêt des configurations multistatiques pour la reconnaissance de cibles a également été démontré dans ces travaux de thèse. / This study deals with multistatic SAS (Synthetic Aperture Sonar) systems. SAS are high resolution imaging systems compared to classical sonar ones. The SAS technique is largly exploited in the monostatic configuration but few studies already exist in multistatic SAS. Thus, the work consists in evaluating resolution and detection performances in bistatic and multistatic configurations. Then, the objective is to compare these performances to monostatic ones. A radar method has been adapted to sonar to compute bistatic performances and this is an original result of this work.The classical algorithm to reconstruct images from acoustical waves lies on the hypothesis that the target is a sum of point scatterers. This hypothesis is not really well adapted to underwater acoustics that is why a new algogorithm has been developped in this study. The new algorithm would be better adapted to scattering diffraction phenomena at the interface between water and target than the classical one. The scattered field model of the target is obtained by combinating boundary integral equations and the Kirchhoff Approximation. An imaging reconstruction method by 2D Fourier Transform of this model has been implemented and tested on numerical and experimental datas. The new algorithm allow a better reconstruction accurency and is able to give quantitative information on targets. The interest of multistatic configurations for target identification has also been demonstrated in this PhD work.

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