Grant R. Gerhart

Bio: Grant R. Gerhart is an academic researcher from United States Department of the Army. The author has contributed to research in topics: Stokes parameters & Unmanned ground vehicle. The author has an hindex of 21, co-authored 145 publications receiving 1425 citations. Previous affiliations of Grant R. Gerhart include University of Michigan & United States Army TACOM Life Cycle Management Command.

Fourier transform channeled spectropolarimetry in the MWIR.

Abstract: A complete Fourier Transform Spectropolarimeter in the MWIR is demonstrated. The channeled spectral technique, originally developed by K. Oka, is implemented with the use of two Yttrium Vanadate (YVO4) crystal retarders. A basic mathematical model for the system is presented, showing that all the Stokes parameters are directly present in the interferogram. Theoretical results are compared with real data from the system, an improved model is provided to simulate the effects of absorption within the crystal, and a modified calibration technique is introduced to account for this absorption. Lastly, effects due to interferometer instabilities on the reconstructions, including nonuniform sampling and interferogram translations, are investigated and techniques are employed to mitigate them.

Phase-locking and frustration in an array of nonlinear spin-torque nano-oscillators

Abstract: We demonstrate that the cooperative dynamics of an array of coupled spin-torque nano-oscillators (STNO) can be controlled by introduction of an additional external phase shift βc between microwave current, which couples STNOs, and microwave voltage on the array. When this external phase shift βc compensates the intrinsic phase shift β0, caused by the STNO nonlinearity, a phase-locking regime with increased output power and vanishing inhomogeneous linewidth broadening is achieved. In the opposite case, when external and intrinsic phase shifts are added, the STNO array demonstrates a frustration regime with low output power and wide and noisy frequency spectrum.

Wavelet-based ground vehicle recognition using acoustic signals

Abstract: We present, in this paper, a wavelet-based acoustic signal analysis to remotely recognize military vehicles using their sound intercepted by acoustic sensors. Since expedited signal recognition is imperative in many military and industrial situations, we developed an algorithm that provides an automated, fast signal recognition once implemented in a real-time hardware system. This algorithm consists of wavelet preprocessing, feature extraction and compact signal representation, and a simple but effective statistical pattern matching. The current status of the algorithm does not require any training. The training is replaced by human selection of reference signals (e.g., squeak or engine exhaust sound) distinctive to each individual vehicle based on human perception. This allows a fast archiving of any new vehicle type in the database once the signal is collected. The wavelet preprocessing provides time-frequency multiresolution analysis using discrete wavelet transform (DWT). Within each resolution level, feature vectors are generated from statistical parameters and energy content of the wavelet coefficients. After applying our algorithm on the intercepted acoustic signals, the resultant feature vectors are compared with the reference vehicle feature vectors in the database using statistical pattern matching to determine the type of vehicle from where the signal originated. Certainly, statistical pattern matching can be replaced by an artificial neural network (ANN); however, the ANN would require training data sets and time to train the net. Unfortunately, this is not always possible for many real world situations, especially collecting data sets from unfriendly ground vehicles to train the ANN. Our methodology using wavelet preprocessing and statistical pattern matching provides robust acoustic signal recognition. We also present an example of vehicle recognition using acoustic signals collected from two different military ground vehicles. In this paper, we will not present the mathematics involved in this research. Instead, the focus of this paper is on the application of various techniques used to achieve our goal of successful recognition.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Excitation of self-localized spin-wave bullets by spin-polarized current in in-plane magnetized magnetic nanocontacts : A micromagnetic study

Abstract: It was shown by micromagnetic simulation that a current-driven in-plane magnetized magnetic nanocontact, besides a quasilinear propagating (``Slonczewski'') spin-wave mode, can also support a nonlinear self-localized spin-wave ``bullet'' mode that exists in a much wider range of bias currents. The frequency of the bullet mode lies below the spectrum of linear propagating spin waves, which makes this mode evanescent and determines its spatial localization. The threshold current for the excitation of the self-localized bullet is substantially lower than for the linear propagating mode, but finite-amplitude initial perturbations of magnetization are necessary to generate a bullet in our numerical simulations, where thermal fluctuations are neglected. Consequently, in these simulations the hysteretic switching between the propagating and localized spin-wave modes is found when the bias current is varied.

A real-time vehicle detection and tracking system in outdoor traffic scenes

Abstract: This work presents a moving vehicle detection and tracking system, MVDT, for real-time operation in outdoor scenes. MVDT consists of three major components: road detection, vehicle detection, and vehicle tracking. The road detection algorithm utilizes a plane-fitting feature, the vehicle detection uses both segmented blob and snakes blob features in a neural network classifier, and a fast vehicle tracking algorithm is designed to locate vehicles in consecutive image frames. We show through experiments that MVDT is effective in detecting moving vehicles in various outdoor scenes and can indeed reach real-time operation requirements.

Model Driven Engineering

Abstract: The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

On-road vehicle detection: a review

Abstract: Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. In these systems, robust and reliable vehicle detection is a critical step. This paper presents a review of recent vision-based on-road vehicle detection systems. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. First, we discuss the problem of on-road vehicle detection using optical sensors followed by a brief review of intelligent vehicle research worldwide. Then, we discuss active and passive sensors to set the stage for vision-based vehicle detection. Methods aiming to quickly hypothesize the location of vehicles in an image as well as to verify the hypothesized locations are reviewed next. Integrating detection with tracking is also reviewed to illustrate the benefits of exploiting temporal continuity for vehicle detection. Finally, we present a critical overview of the methods discussed, we assess their potential for future deployment, and we present directions for future research.

Nonlinear Auto-Oscillator Theory of Microwave Generation by Spin-Polarized Current

Abstract: This paper formulates a general analytic approach to the theory of microwave generation in magnetic nano-structures driven by spin-polarized current and reviews analytic results obtained in this theory. The proposed approach is based on the universal model of an auto-oscillator with negative damping and nonlinear frequency shift. It is demonstrated that this universal model, when applied to the case of a spin-torque oscillator (STO) based on a current-driven magnetic nano-pillar or nano-contact, gives adequate description of most of the experimentally observed properties of STO. In particular, the model describes the power and frequency of the generated microwave signal as functions of the bias current and magnetic field, predicts the magnitude and properties of the generation linewidth, and explains the STO behavior under the influence of periodic and stochastic external signals: frequency modulation, phase-locking to external signals, mutual phase-locking in an array of STO, broadening of the generation linewidth near the generation threshold, etc. The proposed nonlinear auto-oscillator theory is rather general and can be used not only for the development of practical nano-sized STO, but, also, for the description of nonlinear auto-oscillating systems of any physical nature.

Review of snapshot spectral imaging technologies

Abstract: Within the field of spectral imaging, the vast majority of instruments used are scanning devices. Recently, several snapshot spectral imaging systems have become commercially available, providing new functionality for users and opening up the field to a wide array of new applications. A comprehensive survey of the available snapshot technologies is provided, and an attempt has been made to show how the new capabilities of snapshot approaches can be fully utilized.