Radiation Belt Storm Probes (RBSP) Education and Public Outreach Program

The Radiation Belt Storm Probes (RBSP) Education and Public Outreach (E/PO) program serves as a pipeline of activities to inspire and educate a broad audience about Heliophysics and the Sun-Earth system, specifically the Van Allen Radiation Belts. The program is comprised of a variety of formal, informal and public outreach activities that all align with the NASA Education Portfolio Strategic Framework outcomes. These include lesson plans and curriculum for use in the classroom, teacher workshops, internship opportunities, activities that target underserved populations, collaboration with science centers and NASA visitors’ centers and partnerships with experts in the Heliophysics and education disciplines. This paper will detail the activities that make up the RBSP E/PO program, their intended audiences, and an explanation as to how they align with the NASA education outcomes. Additionally, discussions on why these activities are necessary as part of a NASA mission are included. Finally, examples of how the RBSP E/PO team has carried out some of these activities will be discussed throughout.     

Target prescreening based on a quadratic gamma discriminator

This work presents the development, analysis and validation of a new target discrimination module for synthetic aperture radar (SAR) imagery based on an extension of gamma functions to 2-D. Using the two parameter constant false-alarm rate (CFAR) stencil as a prototype, a new stencil based on 2-D gamma functions is used to estimate the intensity of the pixel under test and its surroundings. A quadratic discriminant function is created from these estimates, which is optimally adapted with least squares in a training set of representative clutter and target chips. This discriminator is called the quadratic gamma discriminator (QGD). The combination of the CFAR and the QGD was tested in realistic SAR environments and the results show a large improvement of the false alarm rate with respect to the two-parameter CFAR, both with high resolution (1 ft) fully polarimetric SAR and with one polarization, 1 m SAR data     

Remote infrared observations of parent volatiles in comets: A window on the early solar system

Organic volatiles and water in Oort Cloud comets were investigated at infrared wavelengths. The detected species include H₂O, CO, CH₃OH, CH₄, C₂H₂, C₂H₆, OCS, HCN, NH₃, and H₂CO. Several daughter fragments (CN, OH, NH₂, etc.) are also measured, and OH prompt emission provides a proxy for water. Long-slit spectra are taken at high spectral dispersion and high spatial resolution, eliminating several sources of systematic error. The resulting parent volatile production rates are highly robust, permitting a sensitive search for compositional diversity among comets. Here, seven OC comets are compared. Six (including Halley) exhibit similar compositions (excepting CO and CH₄). Their low formation temperatures (30 K) suggest this group probably formed beyond 30 AU from the young sun. However, C/1999 S4 is severely depleted in hypervolatiles and also in methanol, and it likely formed near 5–10 AU. C/2001 A2 is discussed briefly to illustrate future prospects.     

Studies of target detection algorithms that use polarimetric radardata

Algorithms are described which make use of polarimetric radar information in the detection and discrimination of targets in a ground clutter background. The optimal polarimetric detector (OPD) is derived. This algorithm processes the complete polarization scattering matrix (PSM) and provides the best possible detection performance from polarimetric radar data. Also derived is the best linear polarimetric detector, the polarimetric matched filter (PMF), and the structure of this detector is related to simple polarimetric target types. New polarimetric target and clutter models are described and used to predict the performance of the OPD and the PME. The performance of these algorithms is compared with that of simpler detectors that use only amplitude information to detect targets. The ability to discriminate between target types by exploring differences in polarimetric properties is discussed     

Adaptive filters for detection of targets in foliage

In this paper, we examine three different target detection techniques (including a family of two-dimensional adaptive filters) applied to FOPEN data collected by a UHF foliage penetration radar     

A multiresolution approach to discrimination in SAR imagery

We develop and test a new algorithm for discriminating man-made objects from natural clutter in synthetic-aperture radar (SAR) imagery. This algorithm exploits characteristic variations in speckle pattern as image resolution is varied from course to fine. We model these variations as an autoregression in scale, and then use the autoregressive model to define a multiresolution log-likelihood ratio discriminant. We incorporate this discriminant into the existing Lincoln Laboratory SAR system for automatic target recognition (ATR), and test the augmented system by applying it to millimeter-wave SAR imagery having 0.3 m resolution and representing 56 square kilometers of terrain. At a probability of detection of 0.95, the addition of the multiresolution discriminant reduces the number of natural-clutter false alarms by a factor of six.     

The Acquisition Probability for a Minimum Distance One-Class Classifier

An approximation for the acquisition probability for a minimumdistance one-class classifier is derived. An exact expression for theacquisition probability is dependent upon the operatingcharacteristics in the distance space, the number of targets detected,and the number of other objects detected. An approximateexpression replaces the operating characteristics curve by a singlepoint. Experimental results are presented to demonstrate thevalidity of the approximation. Combinatorial techniques can be usedwhen only the total number of objects detected is known. All ofthese results can be extended to include the multitarget, multipleshotcase.