A recursive multiple model approach to noise identification

Correct knowledge of noise statistics is essential for an estimator or controller to have reliable performance. In practice, however, the noise statistics are unknown or not known perfectly and thus need to be identified. Previous work on noise identification is limited to stationary noise and noise with slowly varying statistics only. An approach is presented here that is valid for nonstationary noise with rapidly or slowly varying statistics as well as stationary noise. This approach is based on the estimation with multiple hybrid system models. As one of the most cost-effective estimation schemes for hybrid system, the interacting multiple model (IMM) algorithm is used in this approach. The IMM algorithm has two desirable properties: it is recursive and has fixed computational requirements per cycle. The proposed approach is evaluated via a number of representative examples by both Monte Carlo simulations and a nonsimulation technique of performance prediction developed by the authors recently. The application of the proposed approach to failure detection is also illustrated     

Data fusion of decentralized local tracker outputs

An approach for fusing offboard track-level data at a central fusion node is presented. The case where the offboard tracker continues to update its local track estimate with measurement and system dynamics models that are not necessarily linear is considered. An algorithm is developed to perform this fusion at a central node without having access to the offboard measurements, their noise statistics, or the location of the local estimator. The algorithm is based on an extension of results that were originally established for linear offboard trackers. A second goal of this work is to develop an inequality constraint for selecting the proper sampling interval for the incoming state estimates to the fusion node. This interval is selected to allow use of conventional Kalman filter algorithms at the fusion node without suffering error performance degradation due to processing a correlated sequence of track state estimates     

The long term variability of 4U 1258-61 (GX304-1)

We present optical spectroscopy and photometry of 4U 1258-61 obtained over the course of six years. Evidence for the evolution of a circumstellar envelope throughout the course of the observations is presented.     

LMC X-4: 13.5 s pulsations and an X-ray flare observed by EXOSAT

EXOSAT observed LMC X-4 on November 17/19, 1983 for one 1.4 day binary period during the high state of the 30.5 day cycle. An eclipse with sharp ingress and slow egress was detected with an eclipse angle of 27.1±1.0 dgr. In the medium energy experiment the source showed a hard power law spectrum. Outside eclipse the source was remarkably constant and only one flare was detected on November 17 at 19 UT lasting for about 1 h. The energy spectrum of the source softens considerably during that time and shows an emission line of cold iron. 13.5 sec pulsations are strongly present during the flare and have also been detected during the quiescent period and during several 1 min flares in another EXOSAT LMC X-4 observation on November 22, 1983. A pulse delay time analysis results in the determination of the pulse period (13.5019±0.0002) s and of the semimajor axis of the orbit of the X-ray star (26.0±0.6) It-sec. These results, together with other available information on LMC X-4, allowed to improve the binary parameters. The mass of the neutron star is found to be 1.34 _±0.44 ^0.48 M_o (95% confidence errors).     

Small-Signal Model for the Series Resonant Converter

The results of a previous discrete-time model of the series resonant dc-dc converter are reviewed and from these a small signal dynamic model is derived. This model is valid for low frequencies and is based on the modulation of the diode conduction angle for control. The basic converter is modeled separately from its output filter to facilitate the use of these results for design purposes. Experimental results are presented.     

Two Methods of Spectral Estimation for SARSAT Signals

Search and rescue satellite aided tracking (SARSAT) depends on the processing of emergency locator transmitter (ELT) signals which are received by a satellite in low polar orbit. Since the signal from a distressed vehicle is normally immersed in a background of other ELT signals (false alarms), interference, and noise, different methods of spectral estimation can provide advantages in estimating carrier frequency. A comparison between average spectrum and minimum spectrum for several real signals is provided here.     

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.     

Nonlinear Adaptive Control of a Synchronous Machine

A nonlinear adaptive controller for a load-commutated brushless dc machine that allows the machine to develop high torque over a wide range of operating conditions, while satisfying voltage and current constraints on both stator and field circuits, is presented. The approach taken is fundamentally different from past work in that a nonlinear control is formulated from the steady-state model of the synchronous machine. Adaptive algorithms are presented for both the unknown load and motor cases.     

GTD Terrain Reflection Model Applied to ILS Glide Scope

The capability of calculating the reflection of electromagnetic signals from uneven terrain has many applications. One of these is the determination of instrument landing system (ILS) glide slope performance. For this application the wavelength is approximately 1 m, incidence angles are usually near grazing, and the fields are horizontally polarized, so that gross irregularities such as dropoffs and hills are more important than surface roughness. Past approaches used to calculate the ground reflections for this application have been three-dimensional physical optics models which were very cumbersome and time consuming and which neglected important diffraction and shadowing phenomenon; a two-dimensional physical optics model which was faster than the three-dimensional models but ignored many shadowing and transverse terrain variation effects; and a half-plane diffraction model which is applicable only to a specified type of terrain geometry. In this paper a terrain reflection model based on the geometrical theory of diffraction (GTD) is described which can accommodate any piecewise linear terrain profile, requires less computer time than the physical optics models, is capable of including transverse terrain effects, and determines the reflected fields with all important diffraction and blockage effects included.