Detection of Coherent Vorticity Structures using Time-Scale Resolved Acoustic Spectroscopy

We describe here an experimental technique based on the acoustic scattering phenomenon allowing the direct probing of the vorticity field in a turbulent flow. Using time-frequency distributions, recently introduced in signal analysis theory, for the analysis of the scattered acoustic signals, we show how the legibility of these signals is significantly improved (time resolved spectroscopy). The method is illustrated on data extracted from a highly turbulent jet flow : discrete vorticity events are clearly evidenced. We claim that the recourse to time-frequency distributions lead to an operational definition of coherent structures associated with phase stationarity in the time-frequency plane.Comment: 26 pages, 6 figures. Latex2e format Revised version : Added references, figures and Changed conten

Passive forward scatter radar based on satellite TV broadcast for air target detection: preliminary experimental results

The focus of this paper is on the detection of airborne targets and on the estimation of their velocity by means of passive forward scatter radar systems based on the DVB-S as transmitter of opportunity. Results related to an experimental campaign carried out near “Leonardo Da Vinci” airport (Rome, Italy) are shown. Particularly the Doppler signature spectrogram is analyzed for a single node FSR configuration and time delay techniques are analyzed for a multi-static configuration suitable for velocity estimation. Obtained results clearly show the feasibility of the DVB-S based FSR configuration to reliably detect aircrafts and the effectiveness of the proposed velocity estimation techniques even in the near field area

Reduction of secondary lobes in joint angle and delay estimation in angle of arrival localization to detect MAC address spoofing in wireless networks

in this paper, we solve the problem of  secondary lobes that are due to noise that comes from constructive and destructive multipath interference that are resulted in received signal strength (RSS) variation over time. This is to develop a very efficient localization algorithm that uses a unique fingerprint angle of arrivals (AOAs), in a specified range, with associated time delays (TDs), in the surrounded sparsity design promoting multipath parameter (i.e:RSS). We solve this problem to detect physical identity spoofing of nodes in radio wireless networks, and localize adversaries and jammers of wireless networks. All radio waves are vulnerable to many types of attacks due to the ability to capture them and sniff or eavesdropping on them in the open space. Physical identity spoofing is used to launch many types of attacks against wireless networks like Denial of Service (DOS), Man-In-The-Middle and Session Hijacking and eavesdropping. Eavesdropping is a human-based social engineering attack. Active adversaries are able to jam and eavesdrop simultaneously, while passive adversaries can only eavesdrop on passed signals. In TCP/IP protocol for example, Media Access Card (MAC) Address is transferred in 802.11 frames. Detection process was carried out by analyzing electromagnetic radio waves that are used to transfer data, in the form of radio wave signals that are formed by the modulation process which mixes the electromagnetic wave, with another one of different frequency or amplitude to produce the signal with a specified pattern of frequency and amplitude. We depended on the angle of arrival of vectors and time delay across scattered areas in the surrounded space to solve the problem of co-location in detection and localization of jammers. We used Maximum Likelihood (ML) angle of arrival determination because ML approaches, known to their higher accuracy and enhanced resolution capabilities. And we assessed their computational complexity that was considered as the major drawback for designers to their implementation in practice.   Our solution was tested on a jammer that changed the signal strength of received signal at the receiver at an angle of arrival 30 degree. And we used scatterers density to determine the angle of arrival of the sender. The simulation has observed that the power of the received signal has changed from the range of angles 20 to 40 degrees. We used scatterers because they describe the density of the signal power, and also enhance the signal to noise ratio, that resulted from the multipath fading of the signal strength. And also overcoming the problem of secondary lobes that are due to signal propagation, while determining the angle of arrival of a signal sender. So, we developed a new passive technique to detect MAC address spoofing based on angle of arrival localization. And assessed the computation complexity of the localization technique through depending on a range angle to estimate the angle of arrival of the adversary within it. And we reduced number of secondary lobes, and their peaks, in the importance function, while determining the angle of arrival, and so increasing the accuracy of angle of arrival measurement. We compared our work to other techniques and find that our technique is better than these techniques

Scattering statistics of rock outcrops: Model-data comparisons and Bayesian inference using mixture distributions

The probability density function of the acoustic field amplitude scattered by the seafloor was measured in a rocky environment off the coast of Norway using a synthetic aperture sonar system, and is reported here in terms of the probability of false alarm. Interpretation of the measurements focused on finding appropriate class of statistical models (single versus two-component mixture models), and on appropriate models within these two classes. It was found that two-component mixture models performed better than single models. The two mixture models that performed the best (and had a basis in the physics of scattering) were a mixture between two K distributions, and a mixture between a Rayleigh and generalized Pareto distribution. Bayes' theorem was used to estimate the probability density function of the mixture model parameters. It was found that the K-K mixture exhibits significant correlation between its parameters. The mixture between the Rayleigh and generalized Pareto distributions also had significant parameter correlation, but also contained multiple modes. We conclude that the mixture between two K distributions is the most applicable to this dataset.Comment: 15 pages, 7 figures, Accepted to the Journal of the Acoustical Society of Americ

Performance evaluation of space-time block coding using a realistic mobile radio channel

This paper presents a performance evaluation of space-time block coding (STBC) employing a realistic mobile radio channel model in macrocellular and urban environments. The bit error rate (BER) is computed by Monte-Carlo simulations in the down-link to evaluate its sensitivity to channel correlation. We consider a horizontal uniform linear array at the base station (BS) formed by up to four antenna elements, and one and two uncorrelated antenna elements at the mobile station (MS). The channel model includes the probability density function (pdf) of the azimuth and delay of the impinging waves and their expected power conditioned on the azimuth and delay. The statistical properties of the model are extracted from macrocellular measurements made in urban environments. Simulation results show that the use of STBC can provide significant gains with acceptable sensitivity to the channel correlation under realistic conditions.Peer ReviewedPostprint (published version