Cross Polarization in Radomes: A Program for Its Computation

A study is made of transmission by radomes, with particular reference to cross polarization, and of the consequent radiation patterns of the radome with its aerial for both linear and circular polarizations. The work is embodied in a computer program which considers a scanner of specifiable size, position, and power distribution at different orientations inside a multilayer radome of given dimensions, class of shape, and construction in terms of the number and properties of its layers. Initially, rays are traced from points on the scanner, and details of their paths and propagation are presented in tables of preliminary results; later, diffraction theory is used. Polar diagrams of cross polarization, of main beam, etc., are presented in final tables for the system. Nearly all the parameters are specifiable, and so the program has reasonably general applicability, and it can also assess the effects of bandwidth, tapering of layer thickness, complex permittivity, and other parameters of the system.     

The Magnetic Field of Mercury

The magnetic field strength of Mercury at the planet’s surface is approximately 1% that of Earth’s surface field. This comparatively low field strength presents a number of challenges, both theoretically to understand how it is generated and observationally to distinguish the internal field from that due to the solar wind interaction. Conversely, the small field also means that Mercury offers an important opportunity to advance our understanding both of planetary magnetic field generation and magnetosphere-solar wind interactions. The observations from the Mariner 10 magnetometer in 1974 and 1975, and the MESSENGER Magnetometer and plasma instruments during the probe’s first two flybys of Mercury on 14 January and 6 October 2008, provide the basis for our current knowledge of the internal field. The external field arising from the interaction of the magnetosphere with the solar wind is more prominent near Mercury than for any other magnetized planet in the Solar System, and particular attention is therefore paid to indications in the observations of deficiencies in our understanding of the external field. The second MESSENGER flyby occurred over the opposite hemisphere from the other flybys, and these newest data constrain the tilt of the planetary moment from the planet’s spin axis to be less than 5°. Considered as a dipole field, the moment is in the range 240 to 270 nT-R _M ³ , where R _M is Mercury’s radius. Multipole solutions for the planetary field yield a smaller dipole term, 180 to 220 nT-R _M ³ , and higher-order terms that together yield an equatorial surface field from 250 to 290 nT. From the spatial distribution of the fit residuals, the equatorial data are seen to reflect a weaker northward field and a strongly radial field, neither of which can be explained by a centered-dipole matched to the field measured near the pole by Mariner 10. This disparity is a major factor controlling the higher-order terms in the multipole solutions. The residuals are not largest close to the planet, and when considered in magnetospheric coordinates the residuals indicate the presence of a cross-tail current extending to within 0.5R _M altitude on the nightside. A near-tail current with a density of 0.1 μA/m² could account for the low field intensities recorded near the equator. In addition, the MESSENGER flybys include the first plasma observations from Mercury and demonstrate that solar wind plasma is present at low altitudes, below 500 km. Although we can be confident in the dipole-only moment estimates, the data in hand remain subject to ambiguities for distinguishing internal from external contributions. The anticipated observations from orbit at Mercury, first from MESSENGER beginning in March 2011 and later from the dual-spacecraft BepiColombo mission, will be essential to elucidate the higher-order structure in the magnetic field of Mercury that will reveal the telltale signatures of the physics responsible for its generation.     

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     

Closed-Form Expressions for Noncoherent Radar Integration Gain and Collapsing Loss

Closed-form formulas allow rapid determination of noncoherent integration gain and integration loss when the single-sample IF signal-to-noise ratio (SNR) is known. In addition, if the required SNR is known for any number of integrated pulses, the required SNR for any other number is easily determined. A closed-form expression is given for radar collapsing loss, expressed in terms of the equivalent integrated signal-to-noise ratio required to produce a given combination of false-alarm and detection probabilities. Alternatively, the single-sample signal-to-noise ratio of a set of samples may be used together with the closed-form expression for integration gain to get the equivalent integrated signal-to-noise ratio.     

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.     

Sequences and arrays with perfect periodic correlation

Properties and methods for synthesizing sequences with perfect periodic autocorrelation functions and good energy efficiency are discussed. The construction is extended to two-dimensional perfect arrays. The construction methods used are based mainly on a search in the frequency domain and on a multiplication theorem for periodic sequences and arrays