On Electrical Equivalence of Aperture-Body and Transmission-Cavity Resonance Phenomena in Subwavelength Conducting Aperture Systems from an Equivalent Circuit Point of View

For a narrow slit structure backed by a conducting strip which is taken as a representative example of an aperture-body resonance (ABR) problem, the transmission resonance condition (i.e., condition for maximum power transmission) and the transmission width (i.e., normalized maximum transmitted power through the slit) are found to be the same as those for narrow slit coupling problem in a thick conducting screen, which is designated as a transmission-cavity resonance (TCR) problem. From a viewpoint of equivalent circuit representation for the transmission resonance condition and the funneling mechanism, the ABR and the TCR problems are thought to be essentially of the same nature.Comment: 14 pages, 3 figure

The Estimation Methods for an Integrated INS/GPS UXO Geolocation System

This work was supported by a project funded by the US Army Corps of Engineers, Strategic Environment Research and Development Program, contract number W912HQ- 08-C-0044.This report was also submitted to the Graduate School of the Ohio State University in partial fulfillment of the PhD degree in Geodetic Science.Unexploded ordnance (UXO) is the explosive weapons such as mines, bombs, bullets, shells and grenades that failed to explode when they were employed. In North America, especially in the US, the UXO is the result of weapon system testing and troop training by the DOD. The traditional UXO detection method employs metal detectors which measure distorted signals of local magnetic fields. Based on detected magnetic signals, holes are dug to remove buried UXO. However, the detection and remediation of UXO contaminated sites using the traditional methods are extremely inefficient in that it is difficult to distinguish the buried UXO from the noise of geologic magnetic sources or anthropic clutter items. The reliable discrimination performance of UXO detection system depends on the employed sensor technology as well as on the data processing methods that invert the collected data to infer the UXO. The detection systems require very accurate positioning (or geolocation) of the detection units to detect and discriminate the candidate UXO from the non-hazardous clutter, greater position and orientation precision because the inversion of magnetic or EMI data relies on their precise relative locations, orientation, and depth. The requirements of position accuracy for MEC geolocation and characterization using typical state-of-the-art detection instrumentation are classified according to levels of accuracy outlined in: the screening level with position tolerance of 0.5 m (as standard deviation), area mapping (less than 0.05 m), and characterize and discriminate level of accuracy (less than 0.02m). The primary geolocation system is considered as a dual-frequency GPS integrated with a three dimensional inertial measurement unit (IMU); INS/GPS system. Selecting the appropriate estimation method has been the key problem to obtain highly precise geolocation of INS/GPS system for the UXO detection performance in dynamic environments. For this purpose, the Extended Kalman Filter (EKF) has been used as the conventional algorithm for the optimal integration of INS/GPS system. However, the newly introduced non-linear based filters can deal with the non-linear nature of the positioning dynamics as well as the non-Gaussian statistics for the instrument errors, and the non-linear based estimation methods (filtering/smoothing) have been developed and proposed. Therefore, this study focused on the optimal estimation methods for the highly precise geolocation of INS/GPS system using simulations and analyses of two Laboratory tests (cart-based and handheld geolocation system). First, the non-linear based filters (UKF and UKF) have been shown to yield superior performance than the EKF in various specific simulation tests which are designed similar to the UXO geolocation environment (highly dynamic and small area). The UKF yields 50% improvement in the position accuracy over the EKF particularly in the curved sections (medium-grade IMUs case). The UKF also performed significantly better than EKF and shows comparable improvement over the UKF when the IMU noise probability iii density function is symmetric and non-symmetric. Also, since the UXO detection survey does not require the real-time operations, each of the developed filters was modified to accommodate the standard Rauch-Tung-Striebel (RTS) smoothing algorithms. The smoothing methods are applied to the typical UXO detection trajectory; the position error was reduced significantly using a minimal number of control points. Finally, these simulation tests confirmed that tactical-grade IMUs (e.g. HG1700 or HG1900) are required to bridge gaps of high-accuracy ranging solution systems longer than 1 second. Second, these result of the simulation tests were validated from the laboratory tests using navigation-grade and medium-grade accuracy IMUs. To overcome inaccurate a priori knowledge of process noise of the system, the adaptive filtering methods have been applied to the EKF and UKF and they are called the AEKS and AUKS. The neural network aided adaptive nonlinear filtering/smoothing methods (NN-EKS and NN-UKS) which are augmented with RTS smoothing method were compared with the AEKS and AUKS. Each neural network-aided, adaptive filter/smoother improved the position accuracy in both straight and curved sections. The navigation grade IMU (H764G) can achieve the area mapping level of accuracy when the gap of control points is about 8 seconds. The medium grade IMUs (HG1700 and HG1900) with NN-AUKS can maintain less than 10cm under the same conditions as above. Also, the neural network aiding can decrease the difference of position error between the straight and the curved section. Third, in the previous simulation test, the UPF performed better than the other filters. However since the UPF needs a large number of samples to represent the a posteriori statistics in high-dimensional space, the RBPF can be used as an alternative to avoid the inefficiency of particle filter. The RBPF is tailored to precise geolocation for UXO detection using IMU/GPS system and yielded improved estimation results with a small number of samples. The handheld geolocation system using HG1900 with a nonlinear filter-based smoother can achieve the discrimination level of accuracy if the update rate of control points is less than 0.5Hz and 1Hz for the sweep and swing respectively. Also, the sweep operation is more preferred than the swing motion because the position accuracy of the sweep test was better than that of the swing test

Real-time delay-multiply-and-sum beamforming with coherence factor for in vivo clinical photoacoustic imaging of humans

In the clinical photoacoustic (PA) imaging, ultrasound (US) array transducers are typically used to provide B-mode images in real-time. To form a B-mode image, delay-and-sum (DAS) beamforming algorithm is the most commonly used algorithm because of its ease of implementation. However, this algorithm suffers from low image resolution and low contrast drawbacks. To address this issue, delay-multiply-and-sum (DMAS) beamforming algorithm has been developed to provide enhanced image quality with higher contrast, and narrower main lobe compared but has limitations on the imaging speed for clinical applications. In this paper, we present an enhanced real-time DMAS algorithm with modified coherence factor (CF) for clinical PA imaging of humans in vivo. Our algorithm improves the lateral resolution and signal-to-noise ratio (SNR) of original DMAS beam-former by suppressing the background noise and side lobes using the coherence of received signals. We optimized the computations of the proposed DMAS with CF (DMAS-CF) to achieve real-time frame rate imaging on a graphics processing unit (GPU). To evaluate the proposed algorithm, we implemented DAS and DMAS with/without CF on a clinical US/PA imaging system and quantitatively assessed their processing speed and image quality. The processing time to reconstruct one B-mode image using DAS, DAS with CF (DAS-CF), DMAS, and DMAS-CF algorithms was 7.5, 7.6, 11.1, and 11.3 ms, respectively, all achieving the real-time imaging frame rate. In terms of the image quality, the proposed DMAS-CF algorithm improved the lateral resolution and SNR by 55.4% and 93.6 dB, respectively, compared to the DAS algorithm in the phantom imaging experiments. We believe the proposed DMAS-CF algorithm and its real-time implementation contributes significantly to the improvement of imaging quality of clinical US/PA imaging system.11Ysciescopu

Observation of chiral quantum-Hall edge states in graphene

In this study, we determined the chiral direction of the quantum-Hall (QH) edge states in graphene by adopting simple two-terminal conductance measurements while grounding different edge positions of the sample. The edge state with a smaller filling factor is found to more strongly interact with the electric contacts. This simple method can be conveniently used to investigate the chirality of the QH edge state with zero filling factor in graphene, which is important to understand the symmetry breaking sequence in high magnetic fields ($\gtrsim$25 T).Comment: 3 pages, 3 figures. Appeared in AP

Dependence of quantum-Hall conductance on the edge-state equilibration position in a bipolar graphene sheet

By using four-terminal configurations, we investigated the dependence of longitudinal and diagonal resistances of a graphene p-n interface on the quantum-Hall edge-state equilibration position. The resistance of a p-n device in our four-terminal scheme is asymmetric with respect to the zero point where the filling factor ($\nu$) of the entire graphene vanishes. This resistance asymmetry is caused by the chiral-direction-dependent change of the equilibration position and leads to a deeper insight into the equilibration process of the quantum-Hall edge states in a bipolar graphene system.Comment: 5 pages, 4 figures, will be published in PR