The Relativistic Proton Spectrometer (RPS) for the Radiation Belt Storm Probes Mission

The Relativistic Proton Spectrometer (RPS) on the Radiation Belt Storm Probes spacecraft is a particle spectrometer designed to measure the flux, angular distribution, and energy spectrum of protons from ～60 MeV to ～2000 MeV. RPS will investigate decades-old questions about the inner Van Allen belt proton environment: a nearby region of space that is relatively unexplored because of the hazards of spacecraft operation there and the difficulties in obtaining accurate proton measurements in an intense penetrating background. RPS is designed to provide the accuracy needed to answer questions about the sources and losses of the inner belt protons and to obtain the measurements required for the next-generation models of trapped protons in the magnetosphere. In addition to detailed information for individual protons, RPS features count rates at a 1-second timescale, internal radiation dosimetry, and information about electrostatic discharge events on the RBSP spacecraft that together will provide new information about space environmental hazards in the Earth’s magnetosphere.     

继续投资航空维修业?

航空维修业正处在发展的十字路口.一些航空公司将其维修业务剥离出去以增加现金流,独立的航空维修企业正在进行调整以应对不断改变的市场环境,更多的维修企业则在寻求新的投资和合作伙伴.     

Characterization and Calibration of the CheMin Mineralogical Instrument on Mars Science Laboratory

A principal goal of the Mars Science Laboratory (MSL) rover Curiosity is to identify and characterize past habitable environments on Mars. Determination of the mineralogical and chemical composition of Martian rocks and soils constrains their formation and alteration pathways, providing information on climate and habitability through time. The CheMin X-ray diffraction (XRD) and X-ray fluorescence (XRF) instrument on MSL will return accurate mineralogical identifications and quantitative phase abundances for scooped soil samples and drilled rock powders collected at Gale Crater during Curiosity’s 1-Mars-year nominal mission. The instrument has a Co X-ray source and a cooled charge-coupled device (CCD) detector arranged in transmission geometry with the sample. CheMin’s angular range of 5^° to 50^° 2θ with <0.35^° 2θ resolution is sufficient to identify and quantify virtually all minerals. CheMin’s XRF requirement was descoped for technical and budgetary reasons. However, X-ray energy discrimination is still required to separate Co?Kα from Co?Kβ and Fe?Kα photons. The X-ray energy-dispersive histograms (EDH) returned along with XRD for instrument evaluation should be useful in identifying elements Z>13 that are contained in the sample. The CheMin XRD is equipped with internal chemical and mineralogical standards and 27 reusable sample cells with either Mylar^? or Kapton^? windows to accommodate acidic-to-basic environmental conditions. The CheMin flight model (FM) instrument will be calibrated utilizing analyses of common samples against a demonstration-model (DM) instrument and CheMin-like laboratory instruments. The samples include phyllosilicate and sulfate minerals that are expected at Gale crater on the basis of remote sensing observations.     

Geometric aspects of long-term noncoherent integration

Long-term integration is defined as integration, perhaps interrupted, over time periods long enough for targets to move through volumes in space resolvable by the radar. Because the motion of the target is unknown prior to detection, long-term integration must be performed along multiple paths representing plausible target paths. The geometry of such a set of integration paths affects detection performance in several ways. The simplest implementation of long-term integration, using constant radial velocity paths, is investigated. The effects of path geometry on detection is quantified and optimized for a target whose motion is nearly radial but otherwise unknown     

Stochastic Dynamic System Suboptimal Control with Uncertain Parameters

The control of a linear system with random coefficients is studied here. The cost function is of a quadratic form and the random coefficients are assumed to be partially observable by the controller. By means of the stochastic Bellman equation, the optimal control of stochastic dynamic models with partially observable coefficients is derived. The optimal control is shown to be a linear function of the observable states and a nonlinear function of random parameters. The theory is applied to an optimal control design of an aircraft landing in wind gust.