Climate Observations - The Instrumental Record

A survey is given of the available instrumental data for monitoring and analysis of climatic variations. We focus on temperature measurements, both over land and ocean, at the surface and aloft.Over land, the older observations were subject to exposure changes which may not have been fully compensated. The effects of urbanization have been largely avoided in studies of climatic change over the last 150 years. There are few records for pre-1850 outside Europe and eastern North America, and the global network shows a recent decline. Over the ocean, sea surface temperature (SST) has been measured using buckets, engine intakes, hull sensors, buoys, and satellites. Many of these data have been effectively homogenized, but new challenges arise as observing systems evolve. Available SST and marine air temperature datasets begin in the 1850s. The data are concentrated in shipping lanes especially before 1900, and very sparse during the world wars, but additional historical data are being digitized.The radiosonde record is short (40 years) and has major gaps over the oceans, tropics and Southern Hemisphere. Instrumental heterogeneities are beginning to be assessed and removed using physical and statistical techniques. The MSU record is complete but only began in 1979, and is not highly resolved in the vertical: major biases, mainly affecting the lower-tropospheric retrieval, have been reduced as a result of recent analyses.Advanced interpolation or data-assimilation techniques are being applied to these data, but the results must be interpreted with care.     

Characterization of Kalman filter residuals in the presence ofmismodeling

The mean and covariance of a Kalman filter residual are computed for specific cases in which the Kalman filter model differs from a linear model that accurately represents the true system (the truth model). Multiple model adaptive estimation (MMAE) uses a bank of Kalman filters, each with a different internal model, and a hypothesis testing algorithm that uses the residuals from this bank of Kalman filters to estimate the true system model. At most, only one Kalman filter model will exactly match the truth model and will produce a residual whose mean and standard deviation have already been analyzed. All of the other filters use internal models that mismodel the true system. We compute the effects of a mismodeled input matrix, output matrix, and state transition matrix on these residuals. The computed mean and covariance are compared with simulation results of flight control failures that correspond to mismodeled input matrices and output matrices     

Ranging airport pseudolite for local area augmentation

This paper discusses the integration of an airport pseudolite (APL) into a local area augmented differential GPS based precision approach system. A prototype architecture is described that is being used to develop requirements for the local area augmentation system. Key features of this prototype system are presented along with its current performance. Key features discussed include the use of a multipath limiting antenna, APL signal structure factors, a unique APL automatic gain control, and GPS blanking technique to maximize APL tracking performance, while minimizing the electromagnetic interference to nominal DGPS performance     

Programmable, multi-purpose opto-electronic sensor system

Optical fibre sensing is becoming increasingly attractive in both the smart structure sphere of interest as well as the medical and industrial concerns. Fibre-optic interferometric sensors can be designed as compact and robust transducers. In general, the transduction mechanism involves the phase modulation of coherent or monochromatic light propagating through a fibre-optic cable, and detecting the changes in the energy associated with this phase change. Sensors based on this technique can generally be configured to be quite sensitive and measurements of a wide variety of physical parameters are achievable. Intrinsic features of optical fibres, such as immunity to electromagnetic interference, flexibility, thinness, strength and weight, make this ideal for sensor technology. In the process of developing fibre-optic sensors for laboratory experimentation, as well as generalised research, an appropriate, easy to use opto-electronic drive and measurement system is required. This paper discusses the operation of a programmable opto-electronic drive and measurement system     

Independent validation and verification of the TCAS II collisionavoidance subsystem

This paper describes the specification-based testing, analysis tools, and associated processes used to independently validate, verify, and ultimately, provide for certifying safety-critical software developed for the Traffic Alert and Collision Avoidance System (TCAS II) program. These tools and processes comprise an effective and Independent Validation and Verification (IV and V) activity applied to the Collision Avoidance Subsystem (GAS) software development process. A requirements specification language called the Requirements State Machine Language (RSML), originally developed by the University of California, Irvine (UCI), was employed for the specification of GAS. The end result is the next generation of TCAS II collision avoidance logic, referred to as Version 7, that is of a higher quality than its predecessors, meets the certification requirements of DO-178B Level B (Ref. 1), and can be shown to satisfy the new operational requirements it was developed to address     

Electronic technical manual development

In the past, Air Force technical manuals have been stored in libraries containing many volumes of such manuals. This article details the creation and development of an Electronic Technical Manual for the F-16 Analog Test Station Sustainment (FATSS) Project. The manual will allow users to search a single CD-ROM to access data on maintenance, operational procedures, self-test, calibration, schematics, and illustrated parts breakdowns     

Embedded information system re-engineering

Currently fielded embedded information systems face readiness challenges imposed by evolving missions and extended service lifespans. The ability to overcome these challenges is constrained by such factors as shrinking budgets, limited computational capacity and diminished manufacturing sources effects that impact both hardware and software options. Wholesale redevelopment is often cost prohibitive, particularly since large portions of embedded applications continue to fulfil mission requirements. Solutions must preserve prior investments while providing efficient pathways for continued technology refresh. A technology solution for affordable modernization of legacy system software is being development. The Embedded Information System Re-engineering (EISR) project is developing an automation-assisted JOVIAL-to-C re-engineering capability that permits simultaneous modernization of both the structure and source language of legacy embedded applications. Engineers will be able to apply the proven labor-saving visualization and analysis features of modern CASE tools to legacy JOVIAL applications. EISR will thus allow the DoD to recapture previous investments in proven legacy algorithms and mission capabilities while permitting the full exploitation of COTS economies of scale. This paper describes in brief the goals and objectives of the EISR project, and provides the current status of the EISR capability.     

Fast converging adaptive processor or a structured covariance matrix

The use of adaptive linear techniques to solve signal processing problems is needed particularly when the interference environment external to the signal processor (such as for a radar or communication system) is not known a priori. Due to this lack of knowledge of an external environment, adaptive techniques require a certain amount of data to cancel the external interference. The number of statistically independent samples per input sensor required so that the performance of the adaptive processor is close (nominally within 3 dB) to the optimum is called the convergence measure of effectiveness (MOE) of the processor. The minimization of the convergence MOE is important since in many environments the external interference changes rapidly with time. Although there are heuristic techniques in the literature that provide fast convergence for particular problems, there is currently not a general solution for arbitrary interference that is derived via classical theory. A maximum likelihood (ML) solution (under the assumption that the input interference is Gaussian) is derived here for a structured covariance matrix that has the form of the identity matrix plus an unknown positive semi-definite Hermitian (PSDH) matrix. This covariance matrix form is often valid in realistic interference scenarios for radar and communication systems. Using this ML estimate, simulation results are given that show that the convergence is much faster than the often-used sample matrix inversion method. In addition, the ML solution for a structured covariance matrix that has the aforementioned form where the scale factor on the identity matrix is arbitrarily lower-bounded, is derived. Finally, an efficient implementation is presented.     

Parametric models for helicopter identification using ANN

An artificial neural network (ANN) based helicopter identification system is proposed. The feature vectors are based on both the tonal and the broadband spectrum of the helicopter signal, ANN pattern classifiers are trained using various parametric spectral representation techniques. Specifically, linear prediction, reflection coefficients, cepstrum, and line spectral frequencies (LSF) are compared in terms of recognition accuracy and robustness against additive noise. Finally, an 8-helicopter ANN classifier is evaluated. It is also shown that the classifier performance is dramatically improved if it is trained using both clean data and data corrupted with additive noise.