Thesis (M.S. in Combat Systems Technology)--Naval Postgraduate School, December 2009. / Thesis Advisor(s): Borden, Brett H. Second Reader: Pace, Phillip E. "December 2009." Description based on title screen as viewed on January 26, 2010. Author(s) subject terms: Radar imaging, moving targets, point spread function, ambiguity function. Includes bibliographical references (p.69). Also available in print.

This dissertation investigates the application of the frequency-scanned beam of a microstrip leaky wave antenna (LWA) to track humans in the two-dimensional (2-D) range-azimuth plane. The history, operating principles and frequency-scanned properties of a microstrip LWA are first reviewed. The basic concept of using a microstrip LWA to track humans is verified by designing, building and testing a broadband microstrip LWA, developing the necessary processing algorithm, and collecting data using a vector network analyzer. A number of topics are then investigated to further advance the concept. First, the idea of combining the frequency-scanned antenna with a short-pulse ultra-wideband (UWB) radar is developed to realize a portable, real-time system for human tracking. The radar concept and the components of the system are discussed in detail. Line-of-sight and through-wall measurements of a human subject are carried out to demonstrate the performance. Second, a new LWA structure is proposed to achieve a narrower azimuth beam, which requires both a small leaky-wave attenuation constant and a long aperture. The transverse resonance method (TRM) is applied to analyze the proposed structure and the results are verified with measurements of a built prototype. Third, a new signal processing technique, compressive sensing, is applied to further improve the resolution in both the azimuth and down range dimensions. The technique is tested with simulation and measurement data and is shown to produce sharper target responses in both the down range and azimuth dimensions. Lastly, the radar cross-section (RCS) of a microstrip LWA is studied. The antenna mode scattering and structural mode scattering are modeled separately. A ray picture is provided to explain the observed time-domain features using the group delay of the leaky wave. / text

This thesis describes the theoretical and practical implementation of a long-range high-resolution millimetre wave imaging radar system to aid with the navigation and guidance of both airborne and ground-based autonomous vehicles. To achieve true autonomy, a vehicle must be able to sense its environment, comprehensively, over a broad range of scales. Objects in the immediate vicinity of the vehicle must be classified at high resolution to ensure that the vehicle can traverse the terrain. At slightly longer ranges, individual features such as trees and low branches must be resolved to allow for short-range path planning. At long range, general terrain characteristics must be known so that the vehicle can plan around difficult or impassable obstructions. Finally, at the largest scale, the vehicle must be aware of the direction to its objective. In the past, short-range sensors based on radar and laser technology have been capable of producing high-resolution maps in the immediate vicinity of the vehicle extending out to a few hundred metres at most. For path planning, and navigation applications where a vehicle must traverse many kilometres of unstructured terrain, a sensor capable of imaging out to at least 3km is required to permit mid and long-range motion planning. This thesis addresses this need by describing the development a high-resolution interrupted frequency modulated continuous wave (FMICW) radar operating at 94GHz. The contributions of this thesis include a comprehensive analysis of both FMCW and FMICW processes leading to an effective implementation of a radar prototype which is capable of producing high-resolution reflectivity images of the ground at low grazing angles. A number of techniques are described that use these images and some a priori knowledge of the area, for both feature and image based navigation. It is shown that sub-pixel registration accuracies can be achieved to achieve navigation accuracies from a single image that are superior to those available from GPS. For a ground vehicle to traverse unknown terrain effectively, it must select an appropriate path from as long a range as possible. This thesis describes a technique to use the reflectivity maps generated by the radar to plan a path up to 3km long over rough terrain. It makes the assumption that any change in the reflectivity characteristics of the terrain being traversed should be avoided if possible, and so, uses a modified form of the gradient-descent algorithm to plan a path to achieve this. The millimetre wave radar described here will improve the performance of autonomous vehicles by extending the range of their high-resolution sensing capability by an order of magnitude to 3km. This will in turn enable significantly enhanced capability and wider future application for these systems.

This thesis describes the theoretical and practical implementation of a long-range high-resolution millimetre wave imaging radar system to aid with the navigation and guidance of both airborne and ground-based autonomous vehicles. To achieve true autonomy, a vehicle must be able to sense its environment, comprehensively, over a broad range of scales. Objects in the immediate vicinity of the vehicle must be classified at high resolution to ensure that the vehicle can traverse the terrain. At slightly longer ranges, individual features such as trees and low branches must be resolved to allow for short-range path planning. At long range, general terrain characteristics must be known so that the vehicle can plan around difficult or impassable obstructions. Finally, at the largest scale, the vehicle must be aware of the direction to its objective. In the past, short-range sensors based on radar and laser technology have been capable of producing high-resolution maps in the immediate vicinity of the vehicle extending out to a few hundred metres at most. For path planning, and navigation applications where a vehicle must traverse many kilometres of unstructured terrain, a sensor capable of imaging out to at least 3km is required to permit mid and long-range motion planning. This thesis addresses this need by describing the development a high-resolution interrupted frequency modulated continuous wave (FMICW) radar operating at 94GHz. The contributions of this thesis include a comprehensive analysis of both FMCW and FMICW processes leading to an effective implementation of a radar prototype which is capable of producing high-resolution reflectivity images of the ground at low grazing angles. A number of techniques are described that use these images and some a priori knowledge of the area, for both feature and image based navigation. It is shown that sub-pixel registration accuracies can be achieved to achieve navigation accuracies from a single image that are superior to those available from GPS. For a ground vehicle to traverse unknown terrain effectively, it must select an appropriate path from as long a range as possible. This thesis describes a technique to use the reflectivity maps generated by the radar to plan a path up to 3km long over rough terrain. It makes the assumption that any change in the reflectivity characteristics of the terrain being traversed should be avoided if possible, and so, uses a modified form of the gradient-descent algorithm to plan a path to achieve this. The millimetre wave radar described here will improve the performance of autonomous vehicles by extending the range of their high-resolution sensing capability by an order of magnitude to 3km. This will in turn enable significantly enhanced capability and wider future application for these systems.

No description available.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 165-173). Available also in a digital version from Dissertation Abstracts.

Thesis (M.S.)--University of Nevada, Reno, 2006. / "May, 2006." Includes bibliographical references (leaf 107). Online version available on the World Wide Web.

No description available.

The Mini-RF radar, launched on the Lunar Reconnaissance Orbiter, imaged the lunar surface using hybrid-polarimetric, transmitting one circular polarization and receiving linear H and V polarizations. Earth-based radar operating at the same frequency has acquired data of the same terrains using circular-polarized transmit waves and sampling circular polarizations. For lunar targets where the viewing geometry is nearly the same, the polarimetry derived from Mini-RF and the earth-based data should be very similar. However, we have discovered that there is a considerable difference in circular polarization ratio (CPR) values between the two data sets. We investigate possible causes for this discrepancy, including cross-talk between channels, sampling, and the ellipticity of the Mini-RF transmit wave. We find that none of these can reproduce the observed CPR differences, though a nonlinear block adaptive quantization function used to compress the data will significantly distort some other polarimetry products. A comparison between earth-based data sets acquired using two different sampling modes (sampling received linear polarizations and sampling circular polarizations) suggests that the CPR differences may be partially due to sampling the data in a different receive polarimetry bases.

Biomedical imaging at microwave frequencies has shown potential for breast cancer detection and monitoring. The advantages of microwave imaging over current imaging techniques are that it is relatively inexpensive, and uses low-energy, non-ionizing radiation. It also provides a quantitative measurement of the dielectric properties of tissues, which offers the ability to characterize tissue types. Microwave imaging also comes with significant drawbacks. The resolution is poor compared to other imaging modalities, which presents challenges when trying to resolve fine structures. It is also not very sensitive to low contrast objects, and the accuracy of recovered tissue properties can be poor. This thesis shows that the use of prior information in microwave imaging inversion algorithms greatly improves the resulting images by minimizing mathematical difficulties in reconstruction that are due to the ill-posed nature of the inverse problem. The focus of this work is to explore novel methods to obtain and use prior information in the microwave breast imaging problem. We make use of finite element contrast source inversion (FEM-CSI) software formulated in two and three dimensions (2D, 3D). This software has the ability to incorporate prior information as an inhomogeneous numerical background medium. We motivate the usefulness of prior information by developing a simulated annealing technique that segments experimental human forearm images into tissue regions. Tissue types are identified and the resulting map of dielectric properties is used as prior information for the 2D FEM-CSI code. This results in improvements to the reconstructions, demonstrating the ability of prior information to improve breast images. We develop a combined microwave tomography/radar algorithm, and demonstrate that it is able to reconstruct images of superior quality, compared to either technique used alone. The algorithm is applied to data from phantoms containing tumours of decreasing size and can accurately monitor the changes. The combined algorithm is shown to be robust to the choice of immersion medium. This property allows us to design an immersion medium-independent algorithm, in which a numerical background can be used to reduce the contrast. We also develop a novel march-on-background technique that reconstructs high quality images using data collected in multiple immersion media. / October 2016