CFAR detection in clutter with unknown correlation properties

We develop a constant false-alarm rate (CFAR) approach for detecting a random N-dimensional complex vector in the presence of clutter or interference modeled as a zero mean complex Gaussian vector whose correlation properties are not known to the receiver. It is assumed that estimates of the correlation properties of the clutter/interference may be obtained independently by processing the received vectors from a set of reference cells. We characterize the detection performance of this algorithm when the signal to be detected is modeled as a zero-mean complex Gaussian random vector with unknown correlation matrix. Results show that for a prescribed false alarm probability and a given signal-to-clutter ratio (to be defined in the text), the detectability of Gaussian random signals depends on the eigenvalues of the matrix R_c^-1R_s. The nonsingular matrix R_c and the matrix R_s are the correlation matrices of clutter-plus-noise and signal vectors respectively. It is shown that the “effective” fluctuation statistics of the signal to be detected is determined completely by the eigenvalues of the matrix R_c^-1R_s. For example the signal to be detected has an effective Swerling II fluctuation statistics when all eigenvalues of the above matrix are equal. Swerling I fluctuation statistics results effectively when all eigenvalues except one are equal to zero. Eigenvalue distributions between these two limiting cases correspond to fluctuation statistics that lie between Swerling I and II models     

Review Article: MHD Wave Propagation Near Coronal Null Points of Magnetic Fields

We present a comprehensive review of MHD wave behaviour in the neighbourhood of coronal null points: locations where the magnetic field, and hence the local Alfvén speed, is zero. The behaviour of all three MHD wave modes, i.e. the Alfvén wave and the fast and slow magnetoacoustic waves, has been investigated in the neighbourhood of 2D, 2.5D and (to a certain extent) 3D magnetic null points, for a variety of assumptions, configurations and geometries. In general, it is found that the fast magnetoacoustic wave behaviour is dictated by the Alfvén-speed profile. In a ??=0 plasma, the fast wave is focused towards the null point by a refraction effect and all the wave energy, and thus current density, accumulates close to the null point. Thus, null points will be locations for preferential heating by fast waves. Independently, the Alfvén wave is found to propagate along magnetic fieldlines and is confined to the fieldlines it is generated on. As the wave approaches the null point, it spreads out due to the diverging fieldlines. Eventually, the Alfvén wave accumulates along the separatrices (in 2D) or along the spine or fan-plane (in 3D). Hence, Alfvén wave energy will be preferentially dissipated at these locations. It is clear that the magnetic field plays a fundamental role in the propagation and properties of MHD waves in the neighbourhood of coronal null points. This topic is a fundamental plasma process and results so far have also lead to critical insights into reconnection, mode-coupling, quasi-periodic pulsations and phase-mixing.     

Acoustic measurements of models of military style supersonic nozzle jets

Modern military aircraft jet engines are designed with variable-geometry nozzles to provide optimal thrust in different operating conditions, depending on the flight envelope. How- ever, acoustic measurements for such nozzles are scarce, due to the cost involved in making full- scale measurements and the lack of details about the exact geometries of these nozzles. Thus the present effort at Pennsylvania State University （PSU） in partnership with GE Aviation and the NASA Glenn Research Center is aiming to study and characterize the acoustic field produced by supersonic jets issuing from converging-diverging military style nozzles, and to identify and test promising noise reduction techniques. An equally important objective is to develop methodology for using data obtained from small- and moderate-scale experiments to reliably predict the full-scale engine noise. The experimental results presented show reasonable agreement between small-scale and medium-scale jets, as well as between heated jets and heat-simulated ones.     

Skylab task and work performance (experiment M-151--time and motion study)

The primary objective of Experiment M151 was to study by means of time and motion analytic techniques the inflight adaptation of Skylab crewmen to a variety of task situations involving different types of activity. A parallel objective was to examine astronaut inflight performance for any behavioral stress effects associated with the working and living conditions of the Skylab environment. Training data provided the basis for comparison of preflight and inflight performance. Efficiency was evaluated through the adaptation function, namely, the relation of performance time over task trials. The results indicate that the initial changeover from preflight to inflight (or, from 1-G to zero-G) was accompanied by a substantial increase in performance time for most work and task activities. Equally important was the finding that crewmen adjusted rapidly to the weightless environment and became proficient in developing techniques with which to optimize task performance. By the end of the second inflight trial, most of the activities were performed almost as efficiently as on the last preflight trial. In addition, the analysis demonstrated the sensitivity of the adaptation function to differences in task and hardware configuration. The function was found to be more regular and less variable inflight than preflight. Translation and control of masses (large or small) were accomplished easily and efficiently through the rapid development of the arms and legs (and the entire body) as subtle guidance and restraint systems. Finally, the adaptation function provided no evidence of behavioral stress effects attributable to the Skylab environment.     

Drag coefficient modeling for grace using Direct Simulation Monte Carlo

Drag coefficient is a major source of uncertainty in predicting the orbit of a satellite in low Earth orbit (LEO). Computational methods like the Test Particle Monte Carlo (TPMC) and Direct Simulation Monte Carlo (DSMC) are important tools in accurately computing physical drag coefficients. However, the methods are computationally expensive and cannot be employed real time. Therefore, modeling of the physical drag coefficient is required. This work presents a technique of developing parameterized drag coefficients models using the DSMC method. The technique is validated by developing a model for the Gravity Recovery and Climate Experiment (GRACE) satellite. Results show that drag coefficients computed using the developed model for GRACE agree to within 1% with those computed using DSMC.