This research investigates signal processing involving a single electromagnetic vector-sensor, with an emphasis on the problem regarding signal-selective narrowband direction-of-arrival (DOA) estimation in the presence of interference. The approach in this thesis relies on a high-resolution ESPRIT-based algorithm. Unlike spatially displaced arrays, the sensor cannot estimate the DOA of sources using phase differences between the array elements, as the elements are spatially co-located. However, the sensor measures the full electromagnetic field vectors, so the DOA can be estimated through the Poynting vector. Limited information is available in the open literature regarding signal-selective DOA estimation for a single electromagnetic vector-sensor. In this thesis, it is shown how the Uni-Vector-Sensor-ESPRIT (UVS-ESPRIT) algorithm that relies on a time-series invariance and was originally devised for deterministic harmonic sources can be applied to non-deterministic sources. Additionally, two algorithms, one based on cyclostationarity and the other based on fourth-order cumulants, are formulated based on the UVS-ESPRIT algorithm and are capable of selectively estimating the source DOA in the presence of interference based on the statistical properties of the sources. The cyclostationarity-based UVS-ESPRIT algorithm is capable of selectively estimating the signal-of-interest DOA when the sources have the same carrier frequency, and thus overlap in frequency. The cumulant-based UVS-ESPRIT algorithm devised for this sensor relies on the independent component analysis algorithm JADE and is capable of selectively estimating the signal-of-interest DOA through the fourth-order cumulants only, is robust to spatially colored noise, and is capable of estimating the DOA of more sources than sensor elements. / Master of Science / Electromagnetic vector-sensors are specialized sensors capable of capturing the full electromagnetic field vectors at a single point in space. Direction-of-arrival (DOA) estimation is the problem of estimating the spatial-angular parameters of one or more wavefronts impinging on an array. For a single electromagnetic vector-sensor, the array elements are not spatially displaced, but it is still possible to estimate the direction-of-arrival through the Poynting vector, which relates the electric and magnetic field vectors to the direction of propagation of an electromagnetic wave. Although direction-of-arrival estimation is a well-established area of research, there is limited discussion in the open literature regarding signal-selective DOA estimation in the presence of interference for a single electromagnetic vector-sensor. This research investigates this problem and discusses how the high-resolution Uni-Vector-Sensor-ESPRIT (UVS-ESPRIT) algorithm may be applied to non-deterministic sources. ESPRIT based algorithms capable of selectively estimating the source DOA are formulated based on the cyclostationarity and higher-order statistics of the sources, which are approaches known to be robust to interference. The approach based on higher-order statistics is also robust to spatially colored noise and is capable of estimating the DOA of more sources than sensor elements. The formulation of the UVS-ESPRIT for higher-order statistics relies on the application of the independent component analysis algorithm JADE, an unsupervised learning technique. Overall, this research investigates signal-selective direction-of-arrival estimation using an ESPRIT-based algorithm for a single electromagnetic vector-sensor.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/99961 |
| Date | 14 September 2020 |
| Creators | Tait, Daniel Beale |
| Contributors | Electrical Engineering, Buehrer, R. Michael, Dhillon, Harpreet Singh, Ellingson, Steven W. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0024 seconds