Coherent change detection with GNSS-based SAR -Experimental study-

Bistatic Synthetic Aperture Radar (BSAR) systems are under an increasing amount of research activity over the last years. The possibility of the use of transmitters of opportunity has increased the flexibility and the applications of radar systems. One of the options is the use of Global Navigation Satellite Systems (GNSS) as transmitters, such as GPS, GLONASS or the forthcoming Galileo and Beidou, that is used in this study. This thesis is the result of the study of a GNSS-based SAR used for detection of changes that may occur in a scene. Although passive SAR is outclassed by active SAR in terms of SAR imaging performance, Coherent Change Detection applications in passive SAR can be promising. A proof-of-concept study is presented in this thesis. The connection between spatial target change and the level of coherence before and after the change is investigated. The stages of theoretical analysis and experimental setup are described in detail. Simulated scenarios are presented and the experimental results are analysed

Passive multi-static SAR with GNSS transmitters:First theoretical and experimental results with point targets

This paper investigates the potential in using a passive multi-static Synthetic Aperture Radar (SAR) with Global Navigation Satellite Systems (GNSS) as transmitters of opportunity. The motivation for this research is based on the concept that a non-coherent combination between multiple bistatic images, obtained by satellites with essentially different angular separations, may yield multi-static imagery with a drastically improved resolution in the range dimension. This concept is confirmed by analytically deriving the multi-static Point Spread Function (MPSF) for this topology. The validity of the analytical results is verified with experimental data. © VDE VERLAG GMBH · Berlin · Offenbach, Germany

Laparoscopic image analysis for robotic arm guidance

Summarization: Some of the most important problems arising during a laparoscopic surgery relate to the limited perception of depth and field of view (fov). In this paper we explore the possibilities of dealing with these problems using appropriate re-modeling of the laparoscopic equipment and image processing algorithms, as to increase the perception ability of the surgeon within the operation space. We demonstrate that by using two camera units and appropriate estimation of the epipolar geometry between the camera views, we can acquire an accurate 3D map of the scene, as well as increased field of view. The benefits for the surgeon include the enhancement of the visible operating space and the increased perception of this space, with the ability of accurately estimating distances of sensitive abdomen regions and organs from the end of the laparoscope tip. Several simulation and real-world experiments are presented as to validate the potential of the proposed schemeΠαρουσιάστηκε στο: 28th Annual International Conference of the Engineering in Medicine and Biology Societ

Simulation model of robotic arm for laparoscopic surgery

Summarization: Many problems that concern the image the surgeon sees arise, during a laparoscopic surgery, such as limited perception of depth and field of view (fov). With a correct modeling of the surgical robot (in our case is the robotic arm AESOP1000) and appropriate image processing algorithms we can give the doctor the ability to have better perception of the space the laparoscope `sees' through its camera(s). One of our objectives deals with robotic arm kinematics and dynamics. AESOP1000 is modeled and simulated through VRML language. We can model an exact virtual space of the patient's abdomen and the trainee can use the robotic arm for a virtual `tour' in it. Using the model, he can observe how the camera is moving in abdomen space but also he can place the camera at every point he wants.Presented on