Sequential threat detection for harbor defense: An x-ray physics-based bayesian approach

Abstract not provide

Particle filtering for signal enhancement in a noisy shallow ocean environment

Abstract not provide

Inverse synthetic aperture radar processing using parametric time-frequency estimators Phase I

This report summarizes the work performed for the Office of the Chief of Naval Research (ONR) during the period of 1 September 1997 through 31 December 1997. The primary objective of this research was aimed at developing an alternative time-frequency approach which is recursive-in-time to be applied to the Inverse Synthethic Aperture Radar (ISAR) imaging problem discussed subsequently. Our short term (Phase I) goals were to: 1. Develop an ISAR stepped-frequency waveform (SFWF) radar simulator based on a point scatterer vehicular target model incorporating both translational and rotational motion; 2. Develop a parametric, recursive-in-time approach to the ISAR target imaging problem; 3. Apply the standard time-frequency short-term Fourier transform (STFT) estimator, initially to a synthesized data set; and 4. Initiate the development of the recursive algorithm. We have achieved all of these goals during the Phase I of the project and plan to complete the overall development, application and comparison of the parametric approach to other time-frequency estimators (STFT, etc.) on our synthesized vehicular data sets during the next phase of funding. It should also be noted that we developed a batch minimum variance translational motion compensation (TMC) algorithm to estimate the radial components of target motion (see Section IV). This algorithm is easily extended to recursive solution and will probably become part of the overall recursive processing approach to solve the ISAR imaging problem. Our goals for the continued effort are to: 1. Develop and extend a complex, recursive-in-time, time- frequency parameter estimator based on the recursive prediction error method (RPEM) using the underlying Gauss- Newton algorithms. 2. Apply the complex RPEM algorithm to synthesized ISAR data using the above simulator. 3. Compare the performance of the proposed algorithm to standard time-frequency estimators applied to the same data sets

An adaptive particle filtering approach to tracking modes in a varying shallow ocean environment

The shallow ocean environment is ever changing mostly due to temperature variations in its upper layers (< 100m) directly affecting sound propagation throughout. The need to develop processors that are capable of tracking these changes implies a stochastic as well as an 'adaptive' design. The stochastic requirement follows directly from the multitude of variations created by uncertain parameters and noise. Some work has been accomplished in this area, but the stochastic nature was constrained to Gaussian uncertainties. It has been clear for a long time that this constraint was not particularly realistic leading a Bayesian approach that enables the representation of any uncertainty distribution. Sequential Bayesian techniques enable a class of processors capable of performing in an uncertain, nonstationary (varying statistics), non-Gaussian, variable shallow ocean. In this paper adaptive processors providing enhanced signals for acoustic hydrophonemeasurements on a vertical array as well as enhanced modal function estimates are developed. Synthetic data is provided to demonstrate that this approach is viable

Model-based processing for shallow ocean environments: The broadband problem

Most acoustic sources found is the ocean environmental are spatially complex and broadband. When propagating in a shallow ocean these source characteristics complicate the analysis of received acoustic data considerably. The enhancement of broadband acoustic pressure- field measurements using a vertical array is discussed. Here a model- based approach is developed for a broadband source using a normal- mode propagation model

Model-Based Signal Processing for Laser Ultrasonic Signal Enhancement

The use of laser-based ultrasonics in the testing of materials and structures offers various advantages over more traditional ultrasonic methods, but is often less sensitive when applied to real materials. Although high energy laser pulses can generate large ultrasonic displacements, nondestructive evaluation requires that the ablation regime be avoided, thus limiting the amount of optical energy which may be used. For this reason, signal processing of laser generated ultrasonic waveforms detected using laser interferometers may be required to extract the desired information from a nondestructive laser ultrasonic test. A model-based signal processing technique offers a way to enhance the signal-to-noise ratios significantly for ultrasonic waveforms obtained using laser-based systems with the generation of the ultrasound occurring in the nondestructive thermoelastic regime

Model-based internal wave processing

A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (dept) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves

GYRO Simulations of Core Momentum Transport in DIII-D and JET Plasmas

Momentum, energy, and particle transport in DIII-D and JET ELMy H-mode plasmas is simulated with GYRO and compared with measurements analyzed using TRANSP. The simulated transport depends sensitively on the nabla(T(sub)i) turbulence drive and the nabla(E(sub)r) turbulence suppression inputs. With their nominal values indicated by measurements, the simulations over-predict the momentum and energy transport in the DIII-D plasmas, and under-predict in the JET plasmas. Reducing |nabla(T(sub)i)| and increasing |nabla(E(sub)r)| by up to 15% leads to approximate agreement (within a factor of two) for the DIII-D cases. For the JET cases, increasing |nabla(T(sub)i)| or reducing |nabla(E(sub)r)| results in approximate agreement for the energy flow, but the ratio of the simulated energy and momentum flows remains higher than measurements by a factor of 2-4

Passive Detection of Narrowband Sources Using a Sensor Array

In this report we derive a model for a highly scattering medium, implemented as a set of MATLAB functions. This model is used to analyze an approach for using time-reversal to enhance the detection of a single frequency source in a highly scattering medium. The basic approach is to apply the singular value decomposition to the multistatic response matrix for a time-reversal array system. We then use the array in a purely passive mode, measuring the response to the presence of a source. The measured response is projected onto the singular vectors, creating a time-reversal pseudo-spectrum. We can then apply standard detection techniques to the pseudo-spectrum to determine the presence of a source. If the source is close to a particular scatterer in the medium, then we would expect an enhancement of the inner product between the array response to the source with the singular vector associated with that scatterer. In this note we begin by deriving the Foldy-Lax model of a highly scattering medium, calculate both the field emitted by the source and the multistatic response matrix of a time-reversal array system in the medium, then describe the initial analysis approach