Studies of the geocenter motion using 16-years DORIS data

An accuracy of geocenter motion estimation is strongly dependent on the geodetic network size and stations distribution over the Earth’s surface. From this point of view DORIS system has an advantage, as its ground network of beacons consists of more than 50 sites, equally distributed over the Earth’s surface. Aiming to study variations of the geocenter movements, the results of DORIS data analysis for the time span 1993.0–2009.0 (inawd06.snx series), performed at the Analysis Centre of the Institute of astronomy of the Russian Academy of Sciences, have been used. DORIS data processing was made with GIPSY/OASIS II software, developed by Jet Propulsion Laboratory and modified for DORIS data processing by Institute Géographique National. Standard deviations of stations coordinates are estimated at the level 0.5–4.0 cm (internal consistency), depending on the number of satellites used in the solution. RMS of estimated components of the DORIS satellites orbits, compared with the solutions of other IDS analysis centres, do not exceed 1–2 cm. Weekly solutions for coordinates have been transformed from free network solutions (inawd06.snx series) to a well defined terrestrial reference frame ITRF2005 with the use of seven parameters of Helmert transformation, which were examined with a view to study variations of the geocenter movements (ina05wd01.geoc time series). In order to estimate linear trend, amplitudes, periods and phases of geocenter variation a method of linear regression was applied. The evaluated amplitudes of annual variations are of the order of 5–7 mm for X and Y components and 27–29 mm for Z component. Semi-annual amplitudes are also noticeable in all components (1–34 mm for X, Y and Z components). Secular trends in the DORIS geocenter coordinates are: −1.2, −0.1 and −0.3 mm/year for X, Y and Z directions respectively.     

High resolution radar clutter statistics

The generalized compound probability density function (GC-pdf) is presented for modeling high resolution radar clutter. In particular, the model is used to describe deviation of the speckle component from the Rayleigh to Weibull or other pdfs with longer tails. The GC-pdf is formed using the generalized gamma (GΓ) pdf to describe both the speckle and the modulation component of the radar clutter. The proposed model is analyzed and thermal noise is incorporated into it. The validation of the GC-pdf with real data is carried out employing the statistical moments as well as goodness-of-fit tests. A large variety of experimental data is used for this purpose. The GC-pdf outperforms the K-pdf in modeling high resolution radar clutter and reveals its structural characteristics     

Neural and fuzzy reconstructors for the virtual flight datarecorder

The results are presented of a comparative study evaluating the performance of neural network (NN) and fuzzy logic reconstructors (FLRs) for the development of a virtual flight data recorder (VFDK). Typical flight data recorders (FDRS) on commercial airliners do not record the aircraft control surface deflections. These dynamic parameters are critical in the investigation of an accident or an uncommanded maneuver. The results are shown relative to a VFDR based on a neural network simulator (NNS) along with a neural network reconstructor (NNR) or a FLR The NNS is trained off-line, using available flight data for the particular aircraft, for the purpose of simulating any desired dynamic output recorded in current FDRs. The NNS is then interfaced with the NNR or with the FLR. The output of the two reconstructors are the control surface deflections which minimize a performance index based on the differences between the available data from the FDR and the output from the NNS. The study tested with night data from a B737-300 shows that both schemes, the one with the NNR and the one with the FLR, provide accurate reconstructions of the control surface deflections time histories     

Multiparametric importance sampling for simulation of radar systems

The performances of the importance sampling (IS) techniques are improved by using multiparametric distortions of the input random processes. The analysis of different constant false-alarm rate (CFAR) algorithms confirms the usefulness of this method. The potential of this new approach is fully exploited if optimization techniques are used to obtain the optimum distortions and to avoid bias in the estimates     

Avionics systems maintenance improvement: a perception

This paper explores the possibility of applying recent developments in various fields of electronics, especially wireless personal communication services, to reduce avionics systems repair cycle time and to generally improve maintenance services. But before scaling these prospects, present-day maintenance services are touched upon and advances in associated technologies are also mentioned     

Advanced materials for next generation NiMH portable, HEV and EVbatteries

While Ovonic NiMH batteries are already in high volume commercial production for portable applications, advances in materials technology have enabled performance improvements in specific energy (100 Wh/kg), specific power (600-1000 W/kg), high temperature operation, charge retention, and voltage stability. Concurrent with technology advances, Ovonic NiMH batteries have established performance and commercial milestones in electric vehicles, hybrid electric vehicles, as well as scooter, motorcycle and bicycle applications. As important as these advances, significant manufacturing cost reductions have also occurred which allow continued growth of NiMH technology. In this paper, advances in performance, applications and cost reduction are discussed with particular emphasis on the improved proprietary metal hydride and nickel hydroxide materials that make such advances possible     

Structures for radar detection in compound Gaussian clutter

The problem of coherent radar target detection in a background of non-Gaussian clutter modeled by a compound Gaussian distribution is studied here. We show how the likelihood ratio may be recast into an estimator-correlator form that shows that an essential feature of the optimal detector is to compute an optimum estimate of the reciprocal of the unknown random local power level. We then proceed to show that the optimal detector may be recast into yet another form, namely a matched filter compared with a data-dependent threshold. With these reformulations of the optimal detector, the problem of obtaining suboptimal detectors may be systematically studied by either approximating the likelihood ratio directly, utilizing a suboptimal estimate in the estimator-correlator structure or utilizing a suboptimal function to model the data-dependent threshold in the matched filter interpretation. Each of these approaches is studied to obtain suboptimal detectors. The results indicate that for processing small numbers of pulses, a suboptimal detector that utilizes information about the nature of the non-Gaussian clutter can be implemented to obtain quasi-optimal performance. As the number of pulses to be processed increases, a suboptimal detector that does not require information about the specific nature of the non-Gaussian clutter may be implemented to obtain quasi-optimal performance     

UWB radar detection of targets in foliage using alpha-stableclutter models

We address the problem of detection of targets obscured by a forest canopy using an ultrawideband (UWB) radar. The forest clutter observed in the radar imagery is a highly impulsive random process that is more accurately modeled with the recently proposed class of alpha-stable processes as compared with Gaussian, Weibull, and K-distribution models. With this more accurate model, segmentation is performed on the imagery into forest and clear regions. Further, a region-adaptive symmetric alpha stable (SαS) constant false-alarm rate (CFAR) detector is introduced and its performance is compared with the Weibull and Gaussian CFAR detectors. The results on real data show that the SαS CFAR performs better than the Weibull and Gaussian CFAR detectors in detecting obscured targets     

Power management and distribution system for a more-electricaircraft (MADMEL)

A five-phase Power Management and Distribution System for a More-Electric Aircraft (MADMEL) program was awarded by the Air Force to Northrop/Grumman Military Aircraft Division in September 1991. The objective of the program is to design, develop, and demonstrate an advanced electrical power generation and distribution system for a More-Electric Aircraft (MEA). The MEA emphasizes the use of electrical power in place of hydraulics, pneumatic, and mechanical power to optimize the performance and life cycle cost of the aircraft. This paper presents an overview of the MADMEL program and a top-level summary of the program results, development and test of major components to date. In Phase I and Phase II studies, the electrical load requirements were established and the electrical power system architecture was defined for both near-term (NT-year 1996) and far-term (FT-year 2003) MEA application. The detailed design and specification for the Electrical Power System (EPS), its interface with the Vehicle Management System, and the test set-up were developed under Phase III. Phase IV, fabrication and testing of the subsystem level hardware, has been completed. Overall system level integration and testing, Phase V, is scheduled to be completed by September 1999     

Simplified Solution for a Class of Fading Memory Filters

A fading memory filter is a least squares estimator (LSE) thatapplies an exponentially decaying weight to past measurements.When compared with a standard Kalman filter, its key advantagesare asymptotic stability and reduced sensitivity to modeling errors.This paper derives a simple solution for a class of fading memoryfilters, resulting in a reduction in computational complexity. Steadystate filter solutions are obtained for second-and third-order filtersused in a global positioning system (GPS) receiver for high dynamicvehicles.