Kalman filtering with state equality constraints

Kalman filters are commonly used to estimate the states of a dynamic system. However, in the application of Kalman filters there is often known model or signal information that is either ignored or dealt with heuristically. For instance, constraints on state values (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. A rigorous analytic method of incorporating state equality constraints in the Kalman filter is developed. The constraints may be time varying. At each time step the unconstrained Kalman filter solution is projected onto the state constraint surface. This significantly improves the prediction accuracy of the filter. The use of this algorithm is demonstrated on a simple nonlinear vehicle tracking problem     

Acceleration of the solar wind

In this review, we discuss critically recent research on the acceleration of the solar wind, giving emphasis to high-speed solar wind streams emanating from solar coronal holes. We first explain why thermally driven wind models constrained by solar and interplanetary observations encounter substantial difficulties in explaining high speed streams. Then, through a general discussion of energy addition to the solar wind above the coronal base, we indicate a possible resolution of these difficulties. Finally, we consider the question of what role MHD waves might play in transporting energy through the solar atmosphere and depositing it in the solar wind, and we conclude by examining, in a simple way, the specific mechanism of solar wind acceleration by Alfvén waves and the related problem of accelerating massive stellar winds with Alfvén waves.Paper presented at the IX-th Lindau Workshop The Source Region of the Solar Wind.On leave from the Auroral Observatory, Institute of Mathematical and Physical Sciences, University of Tromsø, N-9001 Tromsø, Norway.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Recursive mode star identification algorithms

Star identification can be accomplished by several different available algorithms that identify the stars observed by a star tracker. However, efficiency and reliability remain key issues and the availability of new active pixel cameras requires new approaches. Two novel algorithms for recursive mode star identification are presented here. The first approach is derived by the spherical polygon search (SP-search) algorithm, it was used to access all the cataloged stars observed by the sensor field-of-view (FOV) and recursively add/remove candidate cataloged stars according to the predicted image motion induced by camera attitude dynamics. Star identification is then accomplished by a star pattern matching technique which identifies the observed stars in the reference catalog. The second method uses star neighborhood information and a catalog neighborhood pointer matrix to access the star catalog. In the recursive star identification process, and under the assumption of "slow" attitude dynamics, only the stars in the neighborhood of previously identified stars are considered for star identification in the succeeding frames. Numerical tests are performed to validate the absolute and relative efficiency of the proposed methods.     

Statistical Technique for Radar Amplitude Calibration

A statistical technique for amplitude calibration of radar systems is presented. As distinct from the input-output crosscorrelation measurement of a linear system impulse response [1], this technique measures the amplitude transfer function of a memoryless, nonlinear system. A generalized theory is developed and calibration accuracy bounds are derived. Used in the calibration of a modern pulsed radar, the technique is compared with conventional reference pulse calibration. The relative merits of the deterministic and statistical approaches are compared.     

Interacting multiple model tracking with target amplitude feature

A recursive tracking algorithm is presented which uses the strength of target returns to improve track formation performance and track maintenance through target maneuvers in a cluttered environment. This technique combines the interacting multiple model (IMM) approach with a generalized probabilistic data association (PDA), which uses the measured return amplitude in conjunction with probabilistic models for the target and clutter returns. Key tracking decisions can be made automatically by assessing the probabilities of target models to provide rapid and accurate decisions for both true track acceptance and false track dismissal in track formation. It also provides the ability to accurately continue tracking through coordinated turn target maneuvers     

The Galileo Dust Detector

The Galileo Dust Detector is intended to provide direct observations of dust grains with masses between 10^-19 and 10^-9 kg in interplanetary space and in the Jovian system, to investigate their physical and dynamical properties as functions of the distances to the Sun, to Jupiter and to its satellites, to study its interaction with the Galilean satellites and the Jovian magnetosphere. Surface phenomena of the satellites (like albedo variations), which might be effects of meteoroid impacts will be compared with the dust environment. Electric charges of particulate matter in the magnetosphere and its consequences will be studied; e.g., the effects of the magnetic field on the trajectories of dust particles and fragmentation of particles due to electrostatic disruption. The investigation is performed with an instrument that measures the mass, speed, flight direction and electric charge of individual dust particles. It is a multicoincidence detector with a mass sensitivity 10⁶ times higher than that of previous in-situ experiments which measured dust in the outer solar system. The instrument weighs 4.2 kg, consumes 2.4 W, and has a normal data transmission rate of 24 bits s^-1 in nominal spacecraft tracking mode. On December 29, 1989 the instrument was switched-on. After the instrument had been configured to flight conditions cruise science data collection started immediately. In the period to May 18, 1990 at least 168 dust impacts have been recorded. For 81 of these dust grains masses and impact speeds have been determined. First flux values are given.     

Electromechanical Actuation Technology for the All-Electric Aircraft

Electromechanical actuation is a critical element that must be developed and verified to make the all-electric aircraft a viable concept. For several years the Flight Control Division of the Air Force Wright Aeronautical Laboratories has sponsored activities to demonstrate the credibility of electromechanical actuation systems (EMAS) for primary flight control actuation functions. The foundation for these EMAS activities and several electromechanical actuation development programs are described here. One involves the design, fabrication, and laboratory test of a rotary, hingeline electromechanical actuator. Another involves the development and flight test demonstration of a linear electromechanical actuator for controlling an aileron of a C-141 aircraft. A third involves the design and development of a linear electromechanical actuator for missiles having severe performance, temperature, and volumetric requirements. In addition, a brief summary of the results from two aircraft actuation trade studies compare the baseline (conventional) hydraulic flight control system with an all-electric airplane concept including quantitative comparisons of weight, reliability and maintainability, and life cycle costs.     

State Estimation and Divergence Analysis

A growing memory discrete dynamic model for performing temporal extrapolations along a predetermined path in a random field is presented. This dynamic model is used to drive a linear system that is itself driven by discrete white noise. The coupled system is used to derive a state estimation scheme that recursively processes noisy measurements of the system. In addition, using the aforementioned dynamic model as a reference (truth) model, the authors develop a covariance analysis to measure the estimation errors that occur when the dynamics along the path through the field are modeled as a Markov linear model and state estimation is performed using discrete Kalman filtering. The performance evaluation of an inertial navigation system influenced by the Earth's gravity field aboard a maneuvering ship is provided as a specific illustrative example.     

Investigations of Stability & Dynamic Performances of a Current-Injected Regulator

The stability and dynamic performances of a buck/boost regulator employing a current-injected control are examined. Small-signal models for the power state, the multiloop error processor, and the duty-cycle pulse modulator are developed. The error-processor model which incorporates the current-injected loop, the dc loop, and the compensation network permits evaluation of the effects of each individual control loop and their combined efforts toward shaping the performance characteristics of the closed-loop system. Comparisons are made between this modeling approach and earlier approaches. Some important yet subtle dissimilarities are discussed. This model predicts the constant-frequency 50-percent duty-cycle instability which is inherent to the current-injected control.     

On-Line Computer for Transient Turbine Cascade Instrumentation

A 32-channel computer based data acquisition and processing system em has been developed for use with the new type of transient cascade facility at Oxford. This is used for testing turbine blades and nozzle guide vanes at full-scale engine Reynolds and Mach numbers ers with correct wallto-flow temperature ratios. A novel technique for processing transient heat transfer data from thin film surface resistance thermometers has been developed. Measurements of surface ace pressure around blades, and of the upstream turbulence level have been made. The cascade and instrumentation are shown to have advantages both in cost and effectiveness over continuous running cascades.