Antenna Pattern Data Research Articles

Examination of the effectiveness of FF MARS in a CATR through electromagnetic simulation

For more than a decade now, a measurement and post-processing technique involving modal filtering, named mathematical absorber reflection suppression (MARS), has been used very successfully to identify and subsequently extract range reflections in spherical, cylindrical and planar near-field antenna test systems and far-field (FF) and compact antenna test ranges (CATRs). Much of the early work concentrated on verification through experimental testing; however, some additional validation was performed using computational electromagnetic (EM) simulations. These considered first FF and subsequently near-field cases. The recent development of an accurate, flexible EM simulation tool that enables the simulation of `measured' FF pattern data as obtained from using a CATR has, for the first time, permitted the careful verification of the FF-MARS technique for a specified antenna under test (AUT) and CATR combination. This study presents simulated `measured' FF antenna pattern data in the presence of a large scatterer and then verifies the successful extraction of the scattering artefacts. In addition to considering range reflections, feed spill-over is also treated. Results are presented and discussed.

The FengYun-3 Microwave Radiation Imager On-Orbit Verification

The Microwave Radiation Imager (MWRI) on board the FengYun-3A/B satellites observes the Earth atmosphere at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz with each having dual polarization. Its calibration system is uniquely designed with a main reflector viewing both cold and hot calibration targets. Two quasi-optical reflectors are used to reflect the radiation from the hot load and cold space to the main reflector. In the MWRI calibration process, a radiation loss in the beam transmission path must be taken into account. The loss factor in the hot load transmission path is derived using the antenna pattern data measured on ground and satellite data observing over the Amazon forest where the scene temperature is steady and close to the hot load. The instrument nonlinearity factors at different channels are also evaluated over a wide range of brightness temperatures and compared with the results from the ground vacuum test. After a cross-calibration with Windsat data, atmospheric products are derived from MWRI brightness temperatures with the accuracy similar to those from the legacy sensors (e.g., the Special Sensor Microwave/Imager).

Quantitative measures of comparison between antenna pattern data sets

Frequently in test, measurement and development, there is a requirement to compare two or more supposedly identical data sets. These data sets may be acquired as: test data (does the data set fall within a given level of conformance); validation data (do the results confirm the applicability of a test methodology or design process); and calibration data (the data is required to act as a benchmark against which other measurements will be assessed). An example of such data is the far-field three-dimensional radiation pattern of antennas, which may be measured repeatedly on the same or different antenna test ranges. The requirement for objective, quantitative and robust methods of assessing such data, is discussed and confirmed. In addition, the constraints placed on these assessment methods, applied by the nature of the measurement process and the measurand, are highlighted and examined. Data sets that can be used to illustrate the application of these comparison techniques are presented and a preliminary assessment of them made using previously established techniques. These data sets embody a variety of subtle and specific characteristics that stem from particular known error sources. The limitations of these established assessment techniques are discussed and used to motivate the development of newer, more sophisticated analysis, where the data sets are further processed to yield objective measures of comparison. A variety of new assessment techniques that satisfy the aforementioned constraints are then presented and their various merits are compared and contrasted to illustrate their applicability to the classification and analysis of large data sets derived from near-field antenna measurements.

Reconstruction of radio images of the sun obtained by the siberian solar radio telescope

Reconstruction of radio images of the Sun obtained by the Siberian Solar Radio Telescope (SSRT) encounters two main problems. First, since the solar radio images at a wavelength of 5.2 cm have a high contrast, the amplitude–phase distribution in the antenna–feeder section should be known with a very high accuracy. Second, since such images comprise not only bright compact components but also low-contrast diffuse areas, there is a problem of deconvolution of these diffuse sources, which is inherent to the CLEAN algorithm. To solve the first problem, we determine the amplitude–phase distortions by an iterative analysis of the image itself, in which the opposite sidelobes of the point-source response are compared. To suppress the influence of other sources on the response, we analyze several compact sources. The phase distortions are determined from the asymmetry of the sidelobes, and the amplitude distortions, from sidelobe values. The image is corrected in the spatial-spectrum domain after each iteration. On the one hand, the problems encountered when reconstructing extended sources are related to the fact that the CLEAN algorithm requires significant computer resources. On the other hand, reconstructing images of extended areas requires that the number of cycles of this algorithm should be increased. Another problem consists in the fact that the use of the same “clean” antenna pattern for reconstructing compact and extended sources results in appearance of high-frequency distortions of the latter sources. If the CLEAN algorithm is applied, then the computer resources are mainly spent to shift the pattern and to find the maximum of the initial image. We decrease the time necessary for shifting the pattern by excluding the points near the zero value from the antenna-pattern data set and by sorting the remaining data points. The time of finding the maximum was decreased by using a local search window. In addition, we use a number of cutoff levels and search the next maximum in the whole image only after reconstructing the windowed image down to the current cut level. To reconstruct bright compact sources, we use the ”clean” antenna pattern close to the ideal pattern. To reconstruct low-contrast diffuse areas, we use the model patterns obtained by convolving the antenna pattern with the images of extended sources.

AMSU-A antenna pattern corrections

A procedure for making antenna pattern corrections to antenna temperatures of the advanced microwave sounding unit-A (AMSU-A) is developed. Antenna efficiencies, fractions of total power over three different solid-angle regions subtended at the satellite by the Earth (plus atmosphere below 20 km), cold space, and the satellite platform, were calculated at 30 Earth views and four possible cold space calibration positions. These calculated results simplify the process for correcting antenna temperature measurements to retrieve the true brightness temperatures from AMSU-A data. Using the antenna pattern data and a profile of atmospheric brightness temperature, a set of antenna pattern corrections was simulated for each channel at the 30 Earth views and four possible cold space calibration positions. The results show that these corrections can add 0.5 to 2.7 K to the antenna temperatures to retrieve the brightness temperatures and that the cold space calibration temperatures may be raised to 2 K above the nominal cold sky temperature of 2.73 K. Antenna pattern 3-dB beamwidths and main-beam efficiencies were also calculated from the antenna pattern data.

An antenna beam modeling algorithm

A parametric model is presented in this paper which characterizes the beam response behavior of a given antenna for circular, linear vertical, and linear horizontal polarizations. The model parameters are defined by a nonlinear Kalman filtering algorithm which effectively estimates these parameters from measured antenna pattern data. Results of the modeling process are shown and compared against the actual (measured) beam pattern data.

Spectrum Signature Modeling and Data Reduction Techniques Applicable to Airborne Antennas

Information is presented on a modeling technique and on data reduction techniques applicable to obtaining the spectrum signatures of low-gain, low-frequency airborne antennas. The modeling technique demonstrates the degree of simplicity permissible in the fabrication of aircraft scale models on which test antennas are mounted. It is shown that simple geometric shapes employed to represent an aerodynamically shaped aircraft will yield sufficiently accurate information for antenna signature evaluation, thus allowing far-field antenna characteristics to be obtained at a relatively low cost. A brief discussion of an analog-digital converter unit is also included. This unit is employed in the placing of antenna pattern data in a format that is applicable to the Electromagnetic Compatibility Analysis Center (ECAC) computer facilities.