John Norgard

Autofocusing for RF tomography using particle swarm optimization

RF tomography employs geometric diversity to obtain high resolution images of targets, potentially with narrow band waveforms. In order to properly capitalize on this spatial diversity, precise knowledge of the sensor positions is required to sub-wavelength accuracy. While GPS can provide good estimates for these locations, remaining uncertainties distort the images produced and limit their utility. In this paper, an autofocusing approach is proposed to compensate for these uncertainties. A cost function is established for the image by evaluating the sharpness of image sub-regions in the neighborhood of known point-like targets. These targets can be identified either from a knowledge base or by examining preliminary imaging results. The cost function is then minimized by adjusting the estimated sensor positions using particle swarm optimization. The algorithm is shown to significantly improve the quality of RF tomographic images, allowing the separation of closely spaced targets that were severely distorted in uncorrected images. Results are provided for both simulated and measured data. A discussion of potential enhancements and wider applications of the algorithm is also included.

Adaptive tomographic sensors for below ground imaging

Herein, ground penetrating radar and tomography are combined to detect and identify hidden targets, such as underground facilities and bard and deeply buried targets. Past experiences in below-ground imaging is described, current measurement results are presented, and future plans are discussed.

Three-dimensional Microwave Tomography: Waveform diversity and distributed sensors for detecting and imaging buried objects with suppressed electromagnetic interference

Microwave tomographic techniques are described in this paper for developing high-resolution images of buried targets using 3D RF CAT Scans with frequency, angular, and polarization diversity and distributed sensors. Surface-contact sensors are used to collect the tomographic data for relay to a circling UAV and transmission to a remote control site (using layered sensing). 3D imaging algorithms have been developed to detect, image, and characterize buried targets. Distributed transmitters and receivers significantly increase unwanted mutual coupling and EM emissions (EMI) that interfere with signal reception, but also increase image resolution. For Ground Penetration (GPEN), reduced mutual coupling and EMI, and improved signal-to-noise ratios (SNR), can be achieved by embedding the transmitter/receiver sensors underground. Simple surface SAR experiments have been performed to detect deep mine shafts at the Zinc Corporation of America. 2D sensor data have been used to validate the 3D processing algorithms. Scale-model lab tests in the DETECT Chamber at AFRL have also been performed to optimize the tomographic images. In addition, WIPL-D models have been used to simulate the embedded and diverse/distributed sensors and to verify the significant enhancement in the received SNR for GPEN obtained by burying the radiating ring under the surface.

The Electromagnetic Spectrum

The electromagnetic (EM) spectrum consists of all forms of EM radiation, from DC to light to gamma rays. A chart of the EM spectrum can be arranged in order of frequency or wavelength into a number of regions, 1 usually wide in extent, within which the EM waves have some specified common characteristics ( e.g ., those characteristics relating to the production or detection of the radiation). A common example is the spectrum of the radiant energy in the region referred to as white light , which when dispersed by a prism will produce a rainbow of its constituent colors.

Direct infrared measurements of phased array aperture excitations

A thermographic imaging technique has been developed to measure electromagnetic (EM) fields. This technique is applied in this paper to measure the aperture plane fields of large phased array radar antennas and to determine the aperture (source) excitations of the array, i.e., the distribution of the radiated energy over the elements in the aperture plane of the array. These IR measurements, therefore, can be performed on-site at the remote location of the antenna in-the-field to produce a non-distorted image of the field excitations in the aperture plane of the array, which control the overall radiation characteristics of the array. In general, these images can be used for field diagnostics to evaluate the electrical characteristics of the elements of the array, i.e., the state (strength) of the aperture excitations and the condition of the switching circuits (phase shifters and attenuators), which control the radiation pattern of the antenna. The aperture field distribution can be compared to a standard “test pattern” to quickly determine the operational state of each individual element of the array. Individual attenuators and/or phase shifters that produce incorrect element intensities can be easily and quickly identified with this technique. Short-circuited elements at various positions in the array are used to simulate faults in the elements and to test the feasibility of the thermal technique to determine the operational state of the array. Therefore, the overall “state of health” of the array and the need for repair can be determined in-the-field using the IR measurement technique to avoid the expensive and time consuming alternative of dismantling the array and shipping it to a maintenance depot for testing, calibration, and repair on a standard, planar, near-field antenna test range. In this paper, the IR technique is tested in a controlled environment to determine the feasibility of using the IR images as an array diagnostic tool to measure the aperture excitations of large phased array radar antennas.

Adaptive Multi-Sensor Waveform Design for RF Tomographic Sensors

Distributed sensing systems incorporating RF tomography allow a trade-off between spatial and spectral diversity, however a large number of widely spaced sensors is conventionally thought to be required. A practical method of reducing the number of sensor nodes is introduced via the concept of the Virtual Tomographic Array. Furthermore, the geometry of this virtual array is electronically reconfigurable. Optimal resource allocation is accomplished instantaneously, with dynamic control based upon matching sensing modalities to site specific target and clutter observables.

NASA Standard Initiator susceptibility to UHF and S-band radio frequency power and lightning strikes

The NASA Standard Initiator (NSI) is an important piece of pyrotechnic equipment used in many space applications. This paper outlines the results of a series of tests done at UHF and S-Band frequencies to determine NSI susceptibility to Radio Frequency (RF) power. The results show significant susceptibility to pulsed RF power in the S-Band region. Additional testing with lightning pulses injected into the firing line harness, modelling the indirect effects of a lightning strike to a spacecraft, showed no vulnerability.

Computational electromagnetic modeling & simulation of ultra wideband sub-surface sensors for the detection and imaging of buried objects using spatial and spectral diversity

An enhanced remote sensing technique for the detection and identification of deeply buried objects is presented in this paper. A new RF Tomographic Technique is proposed for developing RF CAT Scans of buried objects using spectral and spatial diversity. This imaging technique uses an embedded ring of subsurface radiators as the source of strong underground radiated transmissions. Distributed surface-contact sensors are used to collect the tomographic data for relay to a remote control site. Three-dimensional numerical imaging algorithms have been developed to detect, image, and characterize deeply buried objects. Distributed transmitters and receivers significantly increase unwanted mutual coupling and EM emissions that interfere with signal reception; however, by embedding the transmitters underground, reduced mutual coupling and EM emissions, and improved signal-to-noise ratios, can be achieved. Simple 2D surface SAR experiments over deep mine shafts were performed to validate and verify (V&V) the 3D processing algorithms using 2D surface SAR sensor data. The WIPL-D CEM Code was used to model and simulate (M&S) the embedded and distributed sensors and to verify the significant enhancement in the received signal-to-noise ratio obtained by burying the radiating antennas.

Feature Selected Validation and verification (FSVV) of CEM code predictions using IR thermal images of EM fields

An infrared (IR) thermal measurement technique is presented to independently validate and verify (V&V) numerical codes used for computational electromagnetic (CEM) field predictions using feature selected validation (FSV) routines . The thermal technique is applied in this paper to V&V new aircraft scattering codes. IR thermal images (temperature distributions) of the electromagnetic (EM) field scattered from a simple, canonical aircraft are measured for selected microwave frequencies, angles-of-incidence, and polarizations. Using a color-temperature table calibrated at NIST/Boulder, the temperature distributions are converted into equivalent field-intensity distributions of the scattered EM field being measured. These IR thermal images (thermograms) are compared to the predicted images (contour plots or relief maps) of the scattered fields calculated with a selected CEM simulation code over the same measurement plane to V&V that the field patterns and the intensity levels are correct. In addition, the measured field can be visualized with the IR thermogram images. A ldquopicture-to-picturerdquo correlation code is used to compare the predicted and measured results and to assess and score their similarities. This is the first step in a progressive approach using a suite of CEM codes to compare predicted results of more sophisticated aircraft geometries with the measured results from the IR thermograms to develop confidence in the complementary measurement and simulation methods.