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 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.     

Design for validation

An approach is outlined for the development of ultrareliable avionics for civil air transports using a design-for-validation philosophy that includes rigorous application of formal methods. The basic concept of the methodology is introduced, and the role of formal methods is explored. The impact of the design-for-validation philosophy on the system design process is then demonstrated by two simple examples. More details about the design-for-validation methodology are then given     

CFAR data fusion center with inhomogeneous receivers

Detection systems with distributed sensors and data fusion are increasingly used by surveillance systems. A system formed by N inhomogeneous constant false alarm rate (CFAR) detectors (cell-averaging (CA) and ordered statistic (OS) CFAR detectors) is studied. A recursive formulation of an algorithm that permits a fixed level of false alarms in the data fusion center is presented, to set the optimum individual threshold levels in the CFAR receivers and the optimum `K out of N' decision rule in order to maximize the total probability of detection. The algorithm also considers receivers of different quality or with different communication channel qualities connecting them with the fusion center. This procedure has been applied to several hypothetical networks with distributed CA-CFAR and OS-CFAR receivers and for Rayleigh targets and interference, and it was seen that in general the fusion decision OR rule is not always the best     

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     

Land mobile satellite propagation experiments in Kyoto City

In February of 1990, land mobile satellite propagation experiments were conducted in Kyoto City, Japan, using the Engineering Test Satellite V (ETS-V). The signal transmitted from the satellite was received and recorded at a mobile unit moving in different streets of the downtown area. The streets chosen have typical downtown medium and high rise buildings, electric utility poles, trees, etc., which caused obstruction to the satellite line of sight. The propagation characteristics such as fade/nonfade distribution, joint fade and nonfade distribution, phase distribution, and their dependence on the antenna type are discussed for the measured link. Error characteristics in digital communication for the above link have been qualitatively analyzed on the basis of the measured signal level fluctuation. Effect of interleaving and coding to improve the communication link is also discussed     

An experimental investigation of three eigen DF techniques

The comparative direction-finding (DF) performance of multiple signal classification (MUSIC), ROOT-MUSIC, and estimation of signal parameters via rotational invariance techniques (ESPRIT) is considered. Data were collected from two target transmitters operating simultaneously. The objective of the experiment was to evaluate multipath resolution capability using measurement precision equivalent to that found in modern radio direction-finding systems     

Rational placement and required number of information unmanned aerial systems for on-line monitoring of large territories

An urgent problem of organizing the on-line monitoring of large territories using the information unmanned aerial systems (UAS) is considered. We determine the UAS placement and their necessary number by solving a two-criteria problem on rational covering of the territory by these systems. A man-machine algorithm and an example of the problem solution are presented.     

Online INS/GPS integration with a radial basis function neural network

Most of the present navigation systems rely on Kalman filtering to fuse data from global positioning system (GPS) and the inertial navigation system (INS). In general, INS/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings, including signal blockage for GPS and growth of position errors with time for INS. Present Kalman filtering INS/GPS integration techniques have some inadequacies related to the stochastic error models of inertial sensors, immunity to noise, and observability. This paper aims to introduce a multi-sensor system integration approach for fusing data from INS and GPS utilizing artificial neural networks (ANN). A multi-layer perceptron ANN has been recently suggested to fuse data from INS and differential GPS (DGPS). Although being able to improve the positioning accuracy, the complexity associated with both the architecture of multi-layer perceptron networks and its online training algorithms limit the real-time capabilities of this technique. This article, therefore, suggests the use of an alternative ANN architecture. This architecture is based on radial basis function (RBF) neural networks, which generally have simpler architecture and faster training procedures than multi-layer perceptron networks. The INS and GPS data are first processed using wavelet multi-resolution analysis (WRMA) before being applied to the RBF network. The WMRA is used to compare the INS and GPS position outputs at different resolution levels. The RBF-ANN module is then trained to predict the INS position errors and provide accurate positioning of the moving platform. Field-test results have demonstrated that substantial improvement in INS/GPS positioning accuracy could be obtained by applying the combined WRMA and RBF-ANN modules.     

Practical stabilization in attitude thruster control

The attitude stabilization of a spacecraft using thrusters is considered from a practical point of view, i.e., when actuator constraints, uncertainties and failures, measurement noise, fuel consumption, and inertia matrix uncertainty are considered. A variable structure controller based on sliding modes is obtained first, which guarantees global exponential stability under actuator constraints, uncertainties, and failures. The design is based on a continuous average-proportional torque selection function and a set of feasible sliding surfaces, which may be adapted to improve performance. Exponential convergence towards ultimate bounds is guaranteed when all other practical issues arise.