Space Radiation Damage Measurements in the Earth Synchronous Orbit

For direct measurement of the integrated radiation dose experienced in Earth synchronous orbit, p-i-n diodes were flown as radiation dosimeters on LES-6. The diode, which has a lifetime of 10-4 seconds in the intrinsic region, was originally developed as a neutron dosimeter, but can detect 1-MeV electron fluences as low as 1013 e·cm-2. Observations over three years in orbit are presented.     

Recursive temporal-spatial information fusion with applications totarget identification

Centralized/distributed recursive algorithms for temporal-spatial information integration using the Dempster-Shafer technique are developed. Compared with the Bayesian approach, the Dempster-Shafer technique has the strong capability of handling information uncertainties, which are particularly desirable in many applications. In the centralized integration algorithm, all information is pooled into the central processor and integrated. In contrast, the distributed integration algorithm shares the computational burden among the local processors, which increases the computational efficiency. The developed algorithms are effectively applied to a target identification problem with three sensors: identification of friend-foe-neutral (IFFN), electronic support measurement (ESM), and infrared search and track (IRST)     

Fusion of sensors with dissimilar measurement/tracking accuracies

The case of data fusion of sensors dissimilar in their measurement/tracking errors is considered. It is shown that the fused track performance is similar whether the sensor data are fused at the track level or at the measurement level. The case of a cluster of targets, resolved by one sensor but not the other, is also considered. Under certain conditions the fused track may perform worse than the worst of the sensors. A remedy to this problem through modifications of the association algorithm is presented     

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     

Properties and performance of extended target motion analysis

The problem of target motion analysis (TMA) has been the subject of an important literature. However, present methods use data estimated by a short time analysis (azimuths, Dopplers, etc.). For far sources, the nonstationarities of the array processing outputs, induced by the sources motion, may be simply modeled. This model leads one to consider directly a spatio-temporal TMA. Then new (spatio-temporal) data can be estimated. These estimates correspond to a long time analysis. Further, note that they are estimated independently of the (classical) bearings. In this general framework, the concept of source trajectory replaces the classical instantaneous bearings. Corresponding TMA algorithms are then studied. Then the study of statistical performance is carefully studied     

Italy's contribution, from a medical standpoint, to the space safety of payload scientists, and perspectives for the future

In Italy, the selection of the Italian payload scientists has been performed according to the Spacelab Program of ESA. Twenty-four subjects underwent a screening performed by the Health Service of Italian Air Force. They were requested to pass an exercise test on treadmill and another ten-minute test on centrifuge, subject to the effect of +3 Gz. The authors briefly describe the results of the test. Noteworthy is the determination of Central Flicker Fusion Frequency. This parameter makes it possible to assess the endurance level of the subject, much earlier than other techniques (e.g. EKG). The importance of an accurate preliminary screening is emphasized as well as of successive training periods. Future studies will be undertaken to compare evoked cortical potentials with behaviour parameters of space safety, with a view to setting up a subtle tool of evaluation for both future candidates and payload scientists.     

The construction of gravitational field models on the basis of satellite measurements of gravitational potential derivatives

In [1] expressions were constructed for the derivatives of all the orders of a planet’s gravitational potential with respect to the rectangular coordinates related to the gravity center of a planet. These expressions are series of spherical functions. The coefficients of the series of first-order derivatives depend on two Stokes constants, whereas the coefficients of next-order derivatives are linear combinations of the coefficients of preceding-order derivatives. In the present paper the derived expressions for the first and second potential derivatives are transformed into the form that is most convenient for solving the inverse problem, i.e., evaluating Stokes constants from satellite measurements of these derivatives. Each term of the new series for a derivative depends on a sum of two Stokes constants multiplied by linear combinations of several spherical functions. The new form of the expansions for the potential derivatives makes it possible to calculate Stokes constants by simultaneously applying satellite data either for all three first-order potential derivatives, or for all six second-order derivatives. The constructed series may be applied for modeling the Earth’s gravitational field from the satellite data obtained in the international CHAMP, GRACE, and GOCE missions.     

Variation in the ionospheric propagating factor M(3000)F2 at Ouagadougou,Burkina Faso

We use hourly monthly median values of propagation factor M(3000)F2 data observed at Ouagadougou Ionospheric Observatory (geographic12.4°N, 1.5°W; 5.9^o dip), Burkina Faso (West Africa) during the years Januar1987–December1988 (average F10.7 < 130 × 10⁻²² W/m²/Hz, representative of low solar flux conditions) and for January 1989–December1990 (average F10.7 ? 130 × 10⁻²² W/m²/Hz, representative of high solar epoch) for magnetically quiet conditions to describe local time, seasonal and solar cycle variations of equatorial ionospheric propagation factor M(3000)F2 in the African region. We show that that seasonal trend between solar maximum and solar minimum curves display simple patterns for all seasons and exhibits reasonable disparity with root mean square error (RMSE) of about 0.31, 0.29 and 0.26 for December solstice, June solstice and equinox, respectively. Variability Σ defined by the percentage ratio of the absolute standard deviation to the mean indicates significant dissimilarity for the two solar flux levels. Solar maximum day (10–14 LT) and night (22–02 LT) values show considerable variations than the solar minimum day and night values. We compare our observations with those of the IRI 2007 to validate the prediction capacity of the empirical model. We find that the IRI model tends to underestimate and overestimate the observed values of M(3000)F2, in particular, during June solstice season. There are large discrepancies, mainly during high solar flux equinox and December solstice between dawn and local midnight. On the other hand, IRI provides a slightly better predictions for M(3000)F2 between 0900 and 1500 LT during equinox low and high solar activity and equinox high sunspot number. Our data are of great importance in the area of short-wave telecommunication and ionospheric modeling.     

A new global version of M(3000)F2 prediction model based on artificial neural networks

A new version of global empirical model for the ionospheric propagation factor, M(3000)F2 prediction is presented. Artificial neural network (ANN) technique was employed by considering the relevant geophysical input parameters which are known to influence the M(3000)F2 parameter. This new version is an update to the previous neural network based M(3000)F2 global model developed by Oyeyemi et al. (2007), and aims to address the inadequacy of the International Reference Ionosphere (IRI) M(3000)F2 model (the International Radio Consultative Committee (CCIR) M(3000)F2 model). The M(3000)F2 has been found to be relatively inaccurate in representing the diurnal structure of the low latitude region and the equatorial ionosphere. In particular, the existing hmF2 IRI model is unable to reproduce the sharp post-sunset drop in M(3000)F2 values, which correspond to a sharp post-sunset peak in the peak height of the F2 layer, hmF2. Data from 80 ionospheric stations globally, including a good number of stations in the low latitude region were considered for this work. M(3000)F2 hourly values from 1987 to 2008, spanning all periods of low and high solar activity were used for model development and verification process. The ability of the new model to predict the M(3000)F2 parameter especially in the low latitude and equatorial regions, which is known to be problematic for the existing IRI model is demonstrated.