Performance evaluation for MAP state estimate fusion

This paper presents a quantitative performance evaluation method for the maximum a posteriori (MAP) state estimate fusion algorithm. Under ideal conditions where data association is assumed to be perfect, it has been shown that the MAP or best linear unbiased estimate (BLUE) fusion formula provides the best linear minimum mean squared estimate (LMMSE) given local estimates under the linear Gaussian assumption for a static system. However, for a dynamic system where fusion is recursively performed by the fusion center on local estimates generated from local measurements, it is not obvious how the MAP algorithm will perform. In the past, several performance evaluation methods have been proposed for various fusion algorithms, including simple convex combination, cross-covariance combination, information matrix, and MAP fusion. However, not much has been done to quantify the steady state behavior of these fusion methods for a dynamic system. The goal of this work is to present analytical fusion performance results for MAP state estimate fusion without extensive Monte Carlo simulations, using an approach developed for steady state performance evaluation for track fusion. Two different communication strategies are considered: fusion with and without feedback to the sensors. Analytic curves for the steady state performance of the fusion algorithm for various communication patterns are presented under different operating conditions.     

Wireless interconnection to test instruments

Manufacturers are increasingly offering Ethernet connectivity on their test instruments. An additional benefit of this connection method is the ease of conversion to wireless connectivity. This paper describes the Ethernet interface used in the remote control of a RF power amplifier and describes the conversion to wireless connection.     

Microdosimetric measurements of heavy ion tracks.

The biological effectiveness of radiations depends on the spatial pattern of ionizations and excitations produced by the charged particle tracks involved. Ionizations produced by both the primary ion and by energetic delta rays may contribute to the production of biologically relevant damage and to the concentration of damage which may effect the probability of repair. Although average energy concentration (dose) can be calculated using homogeneous track models, the energy is actually concentrated in small volumes containing segments of the ion and delta ray tracks. These local concentrations are studied experimentally using low pressure proportional counters, and theoretically, using Monte Carlo methods. Small volumes near an ion track may be traversed by a delta ray. If they are, the energy deposited will be similar to that produced by a single electron track in a low-energy x-ray irradiation. The probability of a delta ray interaction occurring decreases with the square of the radial distance from the track. The average energy deposited is the product of this probability and the energy deposited in an interaction. Average energy deposited calculated from measured interaction probability is in good agreement with the results of homogeneous track models.     

Reduced-order multiple model adaptive controller for flexiblespacestructure

The robustness of a moving-bank multiple model adaptive estimator/controller to order reduction in the controller design model is examined. It is shown that the adaptive mechanism and bank-moving logic are not confounded by the effects of unmodeled higher order modes of a large flexible spacestructure. Control characteristics are achieved that are essentially equivalent to those of an artificially informed benchmark controller     

SETI education programs in Australia

This paper discusses and evaluates two innovative SETI education programs conducted at the University of Western Sydney, viz: the SETI Pathways Program and the Life in the Universe Curriculum Project.     

Distributed decision fusion using empirical estimation

The problem of optimal data fusion in multiple detection systems is studied in the case where training examples are available, but no a priori information is available about the probability distributions of errors committed by the individual detectors. Earlier solutions to this problem require some knowledge of the error distributions of the detectors, for example, either in a parametric form or in a closed analytical form. Here we show that, given a sufficiently large training sample, an optimal fusion rule can be implemented with an arbitrary level of confidence. We first consider the classical cases of Bayesian rule and Neyman-Pearson test for a system of independent detectors. Then we show a general result that any test function with a suitable Lipschitz property can be implemented with arbitrary precision, based on a training sample whose size is a function of the Lipschitz constant, number of parameters, and empirical measures. The general case subsumes the cases of nonindependent and correlated detectors.     

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     

An experiment with an S-band radar using pulse compression andrange sidelobe suppression for meteorological measurements

A major technology barrier to the application of pulse compression for the meteorological functions required by a next generation ATC radar is range/time sidelobes which mask and corrupt observations of weak phenomena occurring near areas of strong extended meteorological scatterers. Techniques for suppressing range sidelobes are well known but without prior knowledge of the scattering medium's velocity distribution their performance degrades rapidly in the presence of Doppler. Recent investigations have presented a “doppler tolerant” range sidelobe suppression technique. The thrust of the work described herein is the extension of previous simulations to actual transmitted dispersed/coded waveforms using the S-band surveillance radar located at Rome Laboratory Surveillance Facility. The objectives of the experiment are: 1) to extend the verification of the simulation of the Doppler tolerant technique; and 2) to demonstrate that the radar transmitter, waveform generator, and receiver imperfections do not significantly degrade resolution, performance or reliability of meteorological spectral moment estimates     

ERS-1 radial position refinement by dual crossover analysis with TOPEX/Poseidon

Achieving orbital accuracies in the radial direction for ERS-1 commensurate with those for TOPEX/Poseidon is of utmost importance for the integration of the two altimeter data sets. This paper outlines a procedure whereby the radial orbit error for ERS-1 is recovered as a time series expansion in the form of a finite Fourier series with additional terms for atmospheric drag, solar radiation pressure, and initial state vector mismodelling. Using a least squares collocation method with constraints derived from the JGM2 gravity field co-variance matrix, the radial error is recovered using both dual crossovers and ERS-1 single satellite crossovers. Aggregate arcs are then used to derive the ERS-1 orbit error over the repeat period of 35 days. The results are presented in the improvement of fit in the dual crossover, ERS-1 crossover and altimetry data sets as well as the recovery of an altimeter bias for the two satellites.