Target-Handling Capacity of a Phased-Array Tracking Radar

The factors which affect the target-handling capacity of an agile-beamelectronically scanned multitarget-tracking radar are reviewed and analyze.Consideration is given to the choice of strategy for dwell allocation amongtargets, the choice of trajectory extrapolation algorithms for target tracking, and the determination of saturation target acquisition rates. Emphasisis placed upon radar systems with control computers having limited speed and memory, and recommendations are made for allocation strategy and targetytracking algorithms, based on uniform sampling, to be used in maximizing thetarget-handling capacity in this situation.     

Growth of wheat under one tenth of the atmospheric pressure.

Wheat plants were grown in twin closed growth chambers under normal and reduced atmospheric pressures. For the first 22 days from sowing, the reduced pressure was maintained at 200 hPa, and at 100 hPa for the remaining 27 days until harvest. These pressures were obtained by evacuation of the chamber and adding oxygen (170 and 79 hPa respectively) and carbon dioxide (0.65 and 1.0 hPa respectively; about 2 and 3 times above the control). Eighty-seven per cent of the final dry mass was produce under 100 hPa treatment. Growth and development of wheat are not negatively affected by low pressure treatment. Compared to the control, final dry mass increased by 76%, leaf number by 133%, and ear number by 35%, probably due to elevation of CO2. Shortening of shoot parts and increases in chlorophyll and proteins content are not in accordance with a predicted CO2 effect and could be attributed to the N2 removal and the subsequent alteration in gas diffusion rate.     

Analysis of an adaptive CFAR detector in non-Gaussian interference

Coherent signal detection in non-Gaussian interference is presently of interest in adaptive array applications. Conventional array detection algorithms inherently model the interference with a multivariate Gaussian random vector. However, non-Gaussian interference models are also under investigation for applications where the Gaussian assumption may not be appropriate. We analyze the performance of an adaptive array receiver for signal detection in interference modeled with a non-Gaussian distribution referred to as a spherically invariant random vector (SIRV). We first motivate this interference model with results from radar clutter measurements collected in the Mountain Top Program. Then we develop analytical expressions for the probability of false alarm and the probability of detection for the adaptive array receiver. Our analysis shows that the receiver has constant false alarm rate (CFAR) performance with respect to all the interference parameters. Some illustrative examples are included that compare the detection performance of this CFAR receiver with a receiver that has prior knowledge of the interference parameters     

Large-scale Coronal Heating, Clustering of Coronal Bright Points, and Concentration of Magnetic Flux

By combining quiet-region Fe XII coronal images from SOHO/EIT with magnetograms from NSO/Kitt Peak and from SOHO/MDI, we show that the population of network coronal bright points and the magnetic flux content of the network are both markedly greater under the bright half of the large-scale quiet corona than under the dim half. These results (1) support the view that the heating of the entire corona in quiet regions and coronal holes is driven by fine-scale magnetic activity (microflares, explosive events, spicules) seated low in the magnetic network, and (2) suggest that this large-scale modulation of the magnetic flux and coronal heating is a signature of giant convection cells. This revised version was published online in June 2006 with corrections to the Cover Date.     

Magnetospheric Models and Trajectory Computations

The calculation of particle trajectories in the Earth's magnetic field has been a subject of interest since the time of Störmer. The fundamental problem is that the trajectory-tracing process involves using mathematical equations that have `no solution in closed form'. This difficulty has forced researchers to use the `brute force' technique of numerical integration of many individual trajectories to ascertain the behavior of trajectory families or groups. As the power of computers has improved over the decades, the numerical integration procedure has grown more tractable and while the problem is still formidable, thousands of trajectories can be computed without the expenditure of excessive resources. As particle trajectories are computed and the characteristics analyzed we can determine the cutoff rigidity of a specific location and viewing direction and direction and deduce the direction in space of various cosmic ray anisotropies. Unfortunately, cutoff rigidities are not simple parameters due to the chaotic behavior of the cosmic-ray trajectories in the cosmic ray penumbral region. As the computational problem becomes more manageable, there is still the issue of the accuracy of the magnetic field models. Over the decades, magnetic field models of increasing complexity have been developed and utilized. The accuracy of trajectory calculations employing contemporary magnetic field models is sufficient that cosmic ray experiments can be designed on the basis of trajectory calculations. However, the Earth's magnetosphere is dynamic and the most widely used magnetospheric models currently available are static. This means that the greatest uncertainly in the application of charged particle trajectories occurs at low energies.