Inference of vessel behaviour in the Dutch Coastal North Sea

About one year of coastal AIS (Automatic Identification System) data are analysed for vessel behaviour. The data are obtained from thousands of vessels along the Dutch North Sea coast including the entrance to the main port of Rotterdam. Vessel behaviour is described by a number of basic indicators that can be obtained directly from the AIS messages or from other sensors like radar. It is investigated here if the indicators may be used in e.g. classification algorithms to detect suspicious vessels for the purpose of maritime and border security. In addition, the AIS data are used for a preliminary assessment of the vessel detection possibilities of the recently launched TerraSAR-X satellite when operating in ScanSAR mode

Design and analysis of compressed sensing radar detectors

We consider the problem of target detection from a set of Compressed Sensing (CS) radar measurements corrupted by additive white Gaussian noise. We propose two novel architectures and compare their performance by means of Receiver Operating Characteristic (ROC) curves. Using asymptotic arguments and the Complex Approximate Message Passing (CAMP) algorithm, we characterize the statistics of the l1-norm reconstruction error and derive closed form expressions for both the detection and false alarm probabilities of both schemes. Of the two architectures, we demonstrate that the best performing one consists of a reconstruction stage based on CAMP followed by a detector. This architecture, which outperforms the l1-based detector in the ideal case of known background noise, can also be made fully adaptive by combining it with a conventional Constant False Alarm Rate (CFAR) processor. Using the state evolution framework of CAMP, we also derive Signal to Noise Ratio (SNR) maps that, together with the ROC curves, can be used to design a CS-based CFAR radar detector. Our theoretical findings are confirmed by means of both Monte Carlo simulations and experimental results. © 2012 IEEE

Compressive CFAR Radar Processing

In this paper we investigate the performance of a combined Compressive Sensing (CS) Constant False Alarm Rate (CFAR) radar processor under different interference scenarios using both the Cell Averaging (CA) and Order Statistic (OS) CFAR detectors. Using the properties of the Complex Approximate Message Passing (CAMP) algorithm, we demonstrate that the behavior of the CFAR processor is independent of the combination with the non-linear recovery and therefore its performance can be predicted using standard radar tools. We also compare the performance of the CS CFAR processor to that of an `1-norm detector using an experimental data set

Compressive CFAR radar detection

Abstract—In this paper we develop the first Compressive Sensing (CS) adaptive radar detector. We propose three novel architectures and demonstrate how a classical Constant False Alarm Rate (CFAR) detector can be combined with ℓ1-norm minimization. Using asymptotic arguments and the Complex Approximate Message Passing (CAMP) algorithm we characterize the statistics of the ℓ1-norm reconstruction error and derive closed form expressions for both the detection and false alarm probabilities. We support our theoretical findings with a range of experiments that show that our theoretical conclusions hold even in non-asymptotic setting. We also report on the results from a radar measurement campaign, where we designed ad hoc transmitted waveforms to obtain a set of CS frequency measurements. We compare the performance of our new detection schemes using Receiver Operating Characteristic (ROC) curves. I

A Multidisciplinary Educational Laboratory Based on Meteorite Samples

The Italian national project Piano Lauree Scientifiche (PLS) is addressed to high school students in order to promote their interest in physics and science with the aim of increasing professional vocations and enrollments in scientific faculties. In the PLS framework, at Roma Tre University we developed an itinerant educational laboratory based on meteorites analysis by means of a portable kit. The activity is performed at school and the students are directly involved in the study of meteorite features and in measurements of physical properties of the samples. Students are intriguingly introduced in the scientific method working together in acquisition and analysis of data, and writing a final report. Lessons and laboratories were developed in collaboration between researchers and high school teachers. Thanks to their multidisciplinary character the activities represent an excellent tool for stimulating the interest in different fields of science as astronomy, physics, geology and biology. From a collection of meteorite samples we developed portable kits for a use in the schools. Siderite sections are dried by means of an evaporator, to prepare the samples for a protective coating. Thin sections of meteorite samples are also available for polarized light analysis. In our laboratory a set of instruments enables a multiparametric study of meteorites for both scientific and educational purposes. A 200-1000x microscope and a stereomicroscope are suited to the visual investigation of geological and structural features of meteorite samples. An UV/Vis/NIR spectrophotometer with integrating sphere enables transmission, absorbance and reflectance analysis; coupled with a cryostat, such instrumentation can reproduce thermodynamic conditions similar to the ones in the space. With the aim of such equipment intriguing hands-on activities and scientific researches can be performed on meteorite samples by means of non-destructive methods