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.     

Error Analysis of Space-Stable Inertial Navigation Systems

The error equations for a space-stable inertial navigation system are derived. This is done by directly perturbing the mechanization equations in the inertial frame and then transforming in open-loop fashion to the local-level frame. A rotating inertial platform and velocity and altitude damping are considered. The relations between errors in space-stable and local-level systems are noted. Numerical results are presented for certain random error sources.     

AC/DC converter topologies for the Space Station

A new class of AC/DC converter topologies (Type-1 converters) is described, suitable for use in an advanced single-phase sine-wave voltage, high-frequency power distribution system, of the type that was proposed for a 20 kHz Space Station primary electrical power distribution system. The converter comprises a transformer, a resonant network, a current controller, a diode rectifier, and an output filter. The input AC voltage source is converted into a sinusoidal current source using the resonant network. The output of this current source is rectified by the diode rectifier and is controlled by the current controller. The controlled rectified current is then filtered by the output filter to obtain a constant voltage across the load. Three distinct converter topologies, Type-1A, Type-1B, and Type 1-C, are described, and their performance characteristics are presented. All three types have a close-to-unity rated power factor (greater than 0.98), low total harmonic distortion in input current (less than 5%), and high conversion efficiency (greater than 96%)     

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.     

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.     

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.     

9. The venus ionosphere and solar wind interaction

The current state of knowledge of the chemistry, dynamics and energetics of the upper atmosphere and ionosphere of Venus is reviewed together with the nature of the solar wind-Venus interaction. Because of the weak, though perhaps not negligible, intrinsic magnetic field of Venus, the mutual effects between these regions are probably strong and unique in the solar system. The ability of the Pioneer Venus Bus and Orbiter experiments to provide the required data to answer the questions outstanding is discussed in detail.     

Multipath-adaptive GPS/INS receiver

Multipath interference is one of the contributing sources of errors in precise global positioning system (GPS) position determination. This paper identifies key parameters of a multipath signal, focusing on estimating them accurately in order to mitigate multipath effects. Multiple model adaptive estimation (MMAE) techniques are applied to an inertial navigation system (INS)-coupled GPS receiver, based on a federated (distributed) Kalman filter design, to estimate the desired multipath parameters. The system configuration is one in which a GPS receiver and an INS are integrated together at the level of the in-phase and quadrature phase (I and Q) signals, rather than at the level of pseudo-range signals or navigation solutions. The system model of the MMAE is presented and the elemental Kalman filter design is examined. Different parameter search spaces are examined for accurate multipath parameter identification. The resulting GPS/INS receiver designs are validated through computer simulation of a user receiving signals from GPS satellites with multipath signal interference present The designed adaptive receiver provides pseudo-range estimates that are corrected for the effects of multipath interference, resulting in an integrated system that performs well with or without multipath interference present.     

Medium PRF radar PRF selection using evolutionary algorithms

Evolutionary algorithms are applied to the optimization of pulse repetition frequency (PRF), for both eight-and nine PRFs, in medium PRF radar while considering the detailed effects of sidelobe clutter and many other technical factors. The algorithm presented also ensures that all the solutions produced are fully decodable and have no blind velocities. The evolutionary algorithm was able to identify near-optimum PRF sets for a realistic radar system with only a modest computational effort.