Maximum likelihood azimuth estimation applied to SSR/IFF systems

A conventional (nonmonopulse) secondary surveillance radar (SSR) is significantly cheaper than a monopulse SSR but exhibits much greater azimuthal error, especially when some of the replies are missing. Estimation techniques and their performance are discussed with special reference to SSR applications, and a novel estimator for conventional SSR is described. The proposed technique is a close approximation of the maximum-likelihood estimator (MLE), taking into account the receiver characteristics as well as the missed replies. Estimator performance obtained by analysis and computer simulation is compared with that of conventional estimators that are based on the leading and trailing edges of binary sequences and shows significantly improved accuracy     

Computational approach for investigation of thrust and acoustic performances of present-day nozzles

A computational viewpoint on the problems of design and numerical simulation for the nozzles of modern aircraft turbofan engines is presented. Modern concepts of noise-suppressing nozzles for civil aircraft are reviewed. Examples of application of CFD (computational fluid dynamics) methods to the analysis of nozzle flow structure and assessment of nozzle thrust characteristics are given. Errors of turbulence models in simulation of jets are analyzed. The authors’ experience in simulation of noise-suppressing nozzles for supersonic civil aircrafts is demonstrated. Insufficient accuracy of acoustic analogies for this class of tasks is shown, but a possible area of acoustic analogies application is noted. The essential elements of computational aeroacoustics (CAA) approach and numerical methods characteristic of CAA are reviewed. Numerical methodology for the simulation of nozzle acoustic performance is described in detail, including methods for simulation of near and far field of a nozzle, for generation of input perturbations and for the processing the far-field noise. Results of verification and methodical analysis of this acoustic methodology are presented.     

Image texture synthesis-by-analysis using moving-average models

A synthesis-by-analysis model for texture replication or simulation is presented. This model can closely replicate a given textured image or produce another image that although distinct from the original, has the same general visual characteristics and the same first and second-order gray-level statistics as the original image. The texture synthesis algorithm, proposed contains three distinct components: a moving-average (MA) filter, a filter excitation function, and a gray-level histogram. The analysis portion of the texture synthesis algorithm derives the three from a given image. The synthesis portion convolves the MA filter kernel with the excitation function, adds noise, and modifies the histogram of the result. The advantages of this texture model over others include conceptually and computationally simple and robust parameter estimation, inherent stability, parsimony in the number of parameters, and synthesis through convolution. The authors describe a procedure for deriving the correct MA kernel using a signal enhancement algorithm, demonstrate the effectiveness of the model by using it to mimic several diverse textured images, discuss its applicability to the problem of infrared background simulation, and include detailed algorithms for the implementation of the model     

Robust Kalman filter design for predictive wind shear detection

Severe low-altitude wind shear is a threat to aviation safety. Newly developed airborne sensors measure the radial component of wind along a line directly in front of an aircraft. The authors use optimal estimation theory to define a detection algorithm to warn of hazardous wind shear from these sensors. To achieve robustness, a wind shear detection algorithm must distinguish threatening wind shear from less hazardous gustiness, despite variations in wind shear structure. Statistical analysis methods to refine wind shear detection algorithm robustness are presented. Computational methods predict the ability to warn of severe wind shear and avoid false warning. Comparative capability of the detection algorithm as a function of its design parameters is determined, identifying designs that provide robust detection of severe wind shear     

Multitarget detection using Kalman-based average displacementestimator

The anomaly in the displacement estimates obtained from a low-level Kalman-based average displacement estimator is used to detect multiple targets in a forward-looking infrared (FLIR) scene. The displacement estimates originating from the targets could be associated with the detected multiple targets and an updated estimated position of the target could be obtained. This procedure could be repeated for all targets in the scene to obtain multitarget tracking. The behavior of the expected value of the displacement estimates as a function of the number of iterations is investigated. The behavior of the displacement error covariance matrix and the Kalman gain matrix are discussed as functions of the number of iterations     

The mass and helium discrepancy in massive stars: The case Vela X-1

A NLTE-analysis is presented of high S/N spectra of the optical component of the standard massive X-ray binary Vela X-1. In combination with the orbital parameters we conclude that the optical star is highly helium enriched and is significantly overluminous compared to standard evolutionary tracks of massive accretion stars. We then propose a new accretion model able to explain these features.     

Closed cycle coolers for space applications

Single stage Stirling coolers providing refrigeration at around 80 K have been developed for space use and are now being produced commercially. Development work is now concentrating on multistage coolers for temperatures below 30 K. This paper describes results from a two stage cooler built at the Rutherford Appleton Laboratory and preliminary tests on a closed cycle 4 K cooler.     

The plasma instrumentation for the Galileo Mission

The plasma instrumentation (PLS) for the Galileo Mission comprises a nested set of four spherical-plate electrostatic analyzers and three miniature, magnetic mass spectrometers. The three-dimensional velocity distributions of positive ions and electrons, separately, are determined for the energy-per-unit charge (E/Q) range of 0.9 V to 52 kV. A large fraction of the 4-steradian solid angle for charged particle velocity vectors is sampled by means of the fan-shaped field-of-view of 160°, multiple sensors, and the rotation of the spacecraft spinning section. The fields-of-view of the three mass spectrometers are respectively directed perpendicular and nearly parallel and anti-parallel to the spin axis of the spacecraft. These mass spectrometers are used to identify the composition of the positive ion plasmas, e.g., H⁺, O⁺, Na⁺, and S⁺, in the Jovian magnetosphere. The energy range of these three mass spectrometers is dependent upon the species. The maximum temporal resolutions of the instrument for determining the energy (E/Q) spectra of charged particles and mass (M/Q) composition of positive ion plasmas are 0.5 s. Three-dimensional velocity distributions of electrons and positive ions require a minimum sampling time of 20 s, which is slightly longer than the spacecraft rotation period. The two instrument microprocessors provide the capability of inflight implementation of operational modes by ground-command that are tailored for specific plasma regimes, e.g., magnetosheath, plasma sheet, cold and hot tori, and satellite wakes, and that can be improved upon as acquired knowledge increases during the tour of the Jovian magnetosphere. Because the instrument is specifically designed for measurements in the environs of Jupiter with the advantages of previous surveys with the Voyager spacecraft, first determinations of many plasma phenomena can be expected. These observational objectives include field-aligned currents, three-dimensional ion bulk flows, pickup ions from the Galilean satellites, the spatial distribution of plasmas throughout most of the magnetosphere and including the magnetotail, and ion and electron flows to and from the Jovian ionosphere.     

Modification of the SAR step transform algorithm

When the basic step transform algorithm is used to compress synthetic-aperture radar (SAR) signals in azimuth, the linear FM rate and sampling rate must satisfy certain tight constraints. In practice, these constraints cannot be satisfied and errors are introduced into the compressed SAR image. A modification is described of the basic step transform which incorporates interpolation and resampling into the algorithm. These changes allow the removal of the constraints and make the step transform more useful for the compression of real data. An autofocusing capability is also included, without introducing much additional complexity