An experiment with an S-band radar using pulse compression andrange sidelobe suppression for meteorological measurements

A major technology barrier to the application of pulse compression for the meteorological functions required by a next generation ATC radar is range/time sidelobes which mask and corrupt observations of weak phenomena occurring near areas of strong extended meteorological scatterers. Techniques for suppressing range sidelobes are well known but without prior knowledge of the scattering medium's velocity distribution their performance degrades rapidly in the presence of Doppler. Recent investigations have presented a “doppler tolerant” range sidelobe suppression technique. The thrust of the work described herein is the extension of previous simulations to actual transmitted dispersed/coded waveforms using the S-band surveillance radar located at Rome Laboratory Surveillance Facility. The objectives of the experiment are: 1) to extend the verification of the simulation of the Doppler tolerant technique; and 2) to demonstrate that the radar transmitter, waveform generator, and receiver imperfections do not significantly degrade resolution, performance or reliability of meteorological spectral moment estimates     

Application of Gram-Schmidt algorithm to fully adaptive arrays

The Gram-Schmidt orthogonalization (GSO) algorithm has excellent numerical performance and is readily applicable to systolic implementations such as in a field of adaptive cancellation systems. A modified GSO algorithm for a fully adaptive array is proposed and computer simulations show that the proposed algorithm gives superior performance. A systolic implementation of the proposed GSO algorithm for fully adaptive array is presented. A feedback mode GSO algorithm for use with analog weights is also presented and has been shown to have excellent performance in the presence of weight errors     

Relative positioning of multiple moving platforms using GPS

To obtain subdecimeter level accuracy in relative kinematic positioning, the use of double differenced GPS carrier phase measurement with carrier phase ambiguities fixed to their correct integer values must be adopted. If multiple platforms are available in the configuration, the redundancy provided by the multiplicity of platforms can speed up the time to integer ambiguity fixing while at the same time improve the reliability of the solution. An approach to effectively construct ambiguity constraints through the multiplicity of platforms is presented herein. The use of these ambiguity constraints to position multiple moving platforms with respect to each other is then discussed. A series of simulations and field tests are designed and conducted to investigate the effects of different system parameters on this approach, with a configuration of up to 10 moving platforms. The test results show that the use of ambiguity constraints can improve the time to integer ambiguity fixing by up to 67%, relative to the case when no constraints are used. In addition, the use of ambiguity constraints is found to enhance the ability of the multiple platform system to detect wrong ambiguity fixes.     

Automated video protection, monitoring & detection

The latest generation of computer vision technology is revolutionizing concepts, applications, and products in video surveillance and CCTV. This is of prime relevance to security for large outdoor facilities such as commercial airfields, refineries, power plants, and office/industrial campuses. Most airfields, for example, have open (unfenced) perimeters, high volume heterogeneous traffic, are easily accessed on foot or by water, and exist in areas where regulations providing a safety buffer are difficult to legislate or enforce. And all airfields require 24/7 outdoor monitoring - snow, fog, rain, or shine. Likewise, most high-value facilities appealing to criminals and terrorists are in close proximity to public areas (roads, residences, city, etc.). The appeal of automated real-time surveillance is obvious $maximizing efficiency and effectiveness of security personnel and resources while increasing the probability of preventing a serious security breach. Computer vision based solutions have the potential for very discriminating detection and very low false alarms. The bottom line is that applied computer vision has the potential for the greatest return on investment (ROI), both short-term and long-term.     

Solar and Heliospheric Modulation of Galactic Cosmic Rays

The significance of external influences on the environment of Earth and its atmosphere has become evident during recent years. Especially, on time scales of several hundred years, the cosmogenic isotope concentration during the Wolf-, Spoerer-, Maunder- and Dalton-Minimum indicates an increased cosmic ray flux. Because these grand minima of solar activity coincide with cold periods, a correlation of the Earth climate with the cosmic ray intensities is plausible. Any quantitative study of the effects of energetic particles on the atmosphere and environment of the Earth must address their transport to Earth and their interactions with the Earth’s atmosphere including their filtering by the terrestrial magnetosphere. The first problem is one of the fundamental problems in modern cosmic ray astrophysics, and corresponding studies began in the 1960s based on Parker’s cosmic ray modulation theory taking into account diffusion, convection, adiabatic deceleration, and (later) the drift of energetic particles in the global heliospheric magnetic field. It is well established that all of these processes determining the modulation of cosmic rays are depending on parameters that are varying with the solar magnetic cycle. Therefore, the galactic cosmic ray intensities close to Earth is the result of a complex modulation of the interstellar galactic spectrum within the heliosphere. The modern view of this cosmic ray modulation is summarized in our contribution.     

Covariance matrix estimation for adaptive CFAR detection incompound-Gaussian clutter

We address the estimation of the structure of the covariance matrix and its application to adaptive radar detection of coherent pulse trains in clutter-dominated disturbance modeled as a compound-Gaussian process. For estimation purposes we resort to range cells in spatial proximity with that under test and assume that these cells, free of signal components, can be clustered into groups of data with one and the same value of the texture. We prove that, plugging the proposed estimator of the structure of the covariance matrix into a previously derived detector, based upon the generalized likelihood ratio test (GLRT), leads to an adaptive detector which ensures the constant false alarm rate (CFAR) property with respect to the clutter covariance matrix as well as the statistics of the texture. Finally, we show that this adaptive receiver has an acceptable loss with respect to its nonadaptive counterpart in cases of relevant interest for radar applications     

Microbial processes in frozen food

Deep freezing of food and storage at −19°C is a standard conservation procedure in food technology. The lower limit of growth of bacteria in food is from about −5°C to about −8°C, whereas the reproduction limit of yeasts is 2 to 3°C lower. Storage temperatures above −10°C should therefore not be used. At −18°C, a commonly used storage temperature, no growth of microorganisms will occur. The microorganisms mainly found at the lower growth limit are Pseudomonas sp. and basidiomycete yeasts. The reduction in the number of microorganisms due to freezing, storage, and thawing is not of practical importance. Microbial enzymes, in particular lipases and proteases, are still active at −18°C. Therefore, the quality of raw products and good hygiene at the production site are most important.     

Measuring the matter distribution within z = 0.2 cluster lenses with XMM-Newton

We present an analysis of seven clusters observed by XMM-Newton as part of our survey of 17 most X-ray luminous clusters of galaxies at z  0.2 selected for a comprehensive and unbiased study of the mass distribution in massive clusters. Using the public software FTOOLS and XMMSAS we have set up an automated pipeline to reduce the EPIC MOS and pn spectro-imaging data, optimized for extended sources analysis. We also developped a code to perform intensive spectral and imaging analysis particularly focussing on proper background estimate and removal. XMM-Newton deep spectro-imaging of these clusters allowed us to fit a standard β-model to their gas emission profiles as well as a standard MEKAL emission model to their extracted spectra, and test their inferred characteristics against already calibrated relations.     

On adaptive multiband signal detection with the SMI algorithm

In a nonstationary and/or nonhomogeneous interference environment, an adaptive system for target detection may suffer a severe performance degradation due to the lack of a sufficient amount of data from which the system can learn (estimate) the statistics of the environment. The detection performance of an adaptive system, which employs a frequency diversity (multiband) signaling waveform and a multiband sample matrix inversion algorithm (SMI), is analyzed. By comparison with the corresponding single-band system under the chosen system constraint, it is shown that the multiband system can significantly outperform the single band when the amount of data available from a single frequency band is severely limited by the environment