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.     

Optimal number of phased array faces and signal processors for horizon surveillance

The problem of the optimal number of phased array faces for performing 360/spl deg/ horizon surveillance is considered. Assuming the detection performance is the same in all beam positions and the total number of T/R modules is constant, it is shown that the optimal number of array faces is three. This is true whether the arrays are operating simultaneously or sequentially. A parametric analysis is performed between the number of array faces operating simultaneously and the associated cost of simultaneous operation in terms of the size of the array.     

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     

Design for validation

An approach is outlined for the development of ultrareliable avionics for civil air transports using a design-for-validation philosophy that includes rigorous application of formal methods. The basic concept of the methodology is introduced, and the role of formal methods is explored. The impact of the design-for-validation philosophy on the system design process is then demonstrated by two simple examples. More details about the design-for-validation methodology are then given     

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.     

Carbon dioxide and oxygen budgets of a plant cultural system in a CELSS--a case of cultivation of lettuce and turnips.

In order to collect basic data about CO2 and O2 budgets of a plant cultural system in a CELSS, the variation of the CO2 absorption rates of lettuce and turnips were observed during the growing period, under different conditions. The O2 release rates were deduced from the CO2 absorption rates multiplied by 32/44. As a result, when the light intensity, the photoperiod and the atmospheric CO2 concentration increased, the rates also increased. The effects on the turnips were more significant than those on the lettuce. Turnips at 310 micromoles/m2/s of PPFD, 24 hours of photoperiod and 1100 ppm of CO2 concentration grew most actively in the present experimental conditions. One turnip absorbed 32.3 g CO2 and released 23.5 g O2 for 6 days between 24 days and 30 days after sowing.     

Cometary constraints on the planet forming environment.

Molecular elemental and isotopic abundances of comets provide sensitive diagnostics for models of the primitive solar nebula. New measurements of the N2, NH and NH2 abundances in comets together with the in situ Giotto mass spectrometer and dust analyzer data provide new constraints for models of the comet forming environment in the solar nebula. An inventory of nitrogen-containing species in comet Halley indicates that NH3 and CN are the dominant N carriers observed in the coma gas. The elemental nitrogen abundance in the gas component of the coma is found to be depleted by a factor approximately 75 relative to the solar photosphere. Combined with the Giotto dust analyzer results for the coma dust component, we find for comet Halley Ngas + dust approximately 1/6 the solar value. The measurement of the CN carbon isotope ratio from the bulk coma gas and dust in comet Halley indicates a significantly lower value, 12C/13C = 65 +/- 9 than the solar system value of 89 +/- 2. Because the dominant CN carrier species in comets remains unidentified, it is not yet possible to attribute the low isotope ratio predominantly to the bulk gas or dust components. The large chemical and isotopic inhomogeneities discovered in the Halley dust particles on 1 mu scales are indicative of preserved circumstellar grains which survived processing in the interstellar clouds, and may be related to the presolar silicon carbide, diamond and graphite grains recently discovered in carbonaceous chondrites. Less than 0.1% of the bulk mass in the primitive meteorites studied consists of these cosmically important grains. A larger mass fraction (approximately 5%) of chemically heterogeneous organic grains is found in the nucleus of comet Halley. The isotopic anomalies discovered in the PUMA 1 Giotto data in comet Halley are probably also attributable to preserved circumstellar grains. Thus the extent of grain processing in the interstellar environment is much less than predicted by interstellar grain models, and a significant fraction of comet nuclei (approximately 5%) may be in the form of preserved circumstellar matter. Comet nuclei probably formed in much more benign environments than primitive meteorites.     

Application of Gram-Schmidt algorithm to fully adaptive arrays

The Gram-Schmidt orthogonalization (GSO) algorithm has excellent numerical performance and is readily applicable to systolic implementations such as in a field of adaptive cancellation systems. A modified GSO algorithm for a fully adaptive array is proposed and computer simulations show that the proposed algorithm gives superior performance. A systolic implementation of the proposed GSO algorithm for fully adaptive array is presented. A feedback mode GSO algorithm for use with analog weights is also presented and has been shown to have excellent performance in the presence of weight errors     

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.