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.     

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.     

飞机燃油油量测量及姿态误差修正方法

提出了一种基于 CAD技术的航空燃油油量实时测量方法。采用三维实体造型技术 ,建立了某飞机机翼油箱模型 ,利用油量传感器的输出值及飞机姿态信息 ,对燃油油量进行实时测量及姿态误差修正。     

新型精密狭缝的设计

介绍了一种基于弹性铰链的精密狭缝的设计，加工工艺要求和性能测试结果。根据实际需要，狭缝可以采用水冷结构。     

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     

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