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.     

An optimum filter for direct A/D conversion

The author describes a design procedure to find the optimum finite-impulse-response (FIR) filter coefficients when the characteristics of the bandpass filter preceding the analog-to-digital (A/D) converter are known. A simulation of direct A/D conversion performance shows the improvement over the filter coefficients designed to minimize the maximum error over a specified band of frequencies. DC cancellation may be added to the process with very little change in the coefficients of the optimum FIR filter or its performance.<>     

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.     

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.     

Parallel resonant converter with LLC-type commutation

It is shown that by using a proper transformation of state variables, the third-order system of the parallel resonant converter (PRC) with LLC-type commutation can be analyzed by means of a two-dimensional state-plane diagram. A set of characteristic curves which can be used for the converter design is derived from the analysis. It is shown from these curves that the converter possesses more desirable features than the conventional PRC     

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.     

Nitrogen Isotopes on the Moon: Archives of the Solar and Planetary Contributions to the Inner Solar System

Space Science Reviews - The two isotopes of nitrogen, 14N and 15N, have relative abundances extremely variable among solar system reservoirs such as planets and their atmospheres, primitive and...     

How to Climb the Gravity Wall

Space Science Reviews - What type of gravity satellite mission is required for the time after GRACE and GOCE? Essentially, the variables at our disposal are experiment altitude, compensation of...     

Receiver operating characteristics for the coherent UWB randomnoise radar

An ultrawideband (UWB) random-noise radar operating in the 1-2 GHz frequency band has been developed and held-tested at a 200 m range at the University of Nebraska. A unique heterodyne correlation technique based on a delayed transmitted waveform using a photonic delay line has been used to inject coherence within this system. The performance of this radar, assuming a point target, has been investigated from a statistical point of view by developing the theoretical basis for the system's receiver operating characteristics (ROC). Explicit analytical expressions for the joint probability density function (pdf) of the in-phase (I) and quadrature (Q) components of the receiver output have been derived under the assumption that the input signals are partially correlated Gaussian processes. The pdf and the complementary cumulative distribution function (cdf) for the envelope of the receiver output are also derived. These expressions are used to relate the probability of detection (P_d) to the probability of false alarm (P_f ) for different numbers of integrated samples, and the results are analyzed