Dr. Maria Sabrina Greco, Associate Professor at University of Pisa (2016-10-18)
For several decades, the Gaussian assumption on the disturbance modeling in radar systems has been widely used to deal with detection problems. But, in modern high-resolution radar systems, the disturbance cannot be modeled as Gaussian distributed and the classical detectors suffer from high losses. In this talk, after a brief description of modern statistical and spectral models for high-resolution clutter, coherent optimum and sub-optimum detectors, designed for such a background, will be presented and their performance analyzed against a non-Gaussian disturbance. Different interpretations of the various detectors are provided that highlight the relationships and the differences among them. After this first part, some discussion will be dedicated to how to make adaptive the detectors, by incorporating a proper estimate of the disturbance covariance matrix. Recent works on Maximum Likelihood and robust covariance matrix estimation have proposed different approaches such as the Approximate ML (or Fixed-Point) Estimator or the M-estimators. These techniques allow to improve the detection performance in terms of false alarm regulation and detection gain in SNR. Some of results with simulated and real recorded data will be shown.
Presentation Slides: Register
Ed Gellender, Northrop Grumman (2014-07-02)
A historical review and a discussion on the anticipated future of SSR/IFF, puts this subject into perspective. Time-tested legacy techniques are explored, as well as some of the most recent technologies. Specific topics covered include IFF antenna patterns, frequency and spectrum usage, civil air traffic control, military command and control (including Mode 5), new collision avoidance systems, and FAA NextGen air traffic control.
Presentation Slides: PDF - click to view (1.1 MB)
Daniela Viviana Vladutescu, NYCCT/CUNY (2013-10-02)
Today’s remote sensing activities can broadly be subdivided into active and passive remote sensing from the Earth's surface and/or from satellites. Active collection emits energy in order to scan objects and areas whereupon a sensor then detects and measures the radiation that is reflected or backscattered from the target. RADAR is an example of active remote sensing where the time delay between emission and return is measured, establishing the location, height, speed and direction of an object. In passive remote sensing, the source of information is scattered and/or absorbed solar and emitted thermal radiation that allows clues on climate system components through their spectrally variable response.
In terms of observation platforms satellites provide valuable opportunities for collecting global fields of many climate system variables. Airborne field measurement campaigns offer an adequate opportunity to develop new remote sensing algorithms and to define demands of new satellite missions. In addition, surface based measurements allow better controlled and temporally higher resolving measurements, especially of boundary layer and lower atmosphere quantities. Several of these "new" observing systems are now developed into reliable systems for routine standard observations, that are more and more recognized as valuable tools for the observation of relevant climate processes on various scales in time and space, space surveillance and target detection.
Presentation Slides: PDF - click to view (3.4 MB)