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Angle of Arrival (AoA) CALEN CARABAJAL EECS 823

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Introduction to Angle of Arrival Physics Angle between propagation direction of an incident wave and some reference direction (orientation) Plane wave impinging upon array

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Visual Understanding Plane wave impinges on array of antennas with the same orientation and radiation pattern Time delay corresponds to a phase shift between antennas To the right, red lines represent wave front, each with the same relative phase Red dot corresponds incidence of wave front Results in a zero-valued response for this phase

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Wave Propagation and Antenna: Specific Case

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Antenna Arrays, Steering Vector

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Applications of Angle of Arrival Estimation: Wireless Sensor Networks Wireless Sensor Networks May use antenna array on each sensor node Geodesic location of cell phones Emergency phone calls

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Applications of Angle of Arrival: Remote Sensing AoA estimation provides also allows further characterization of target. Adaptive processes can take advantage of this knowledge Beamsteering/Nullsteering Angle-of-arrival-assisted Radio Interferometry Ground moving objects Coupled with other data (range, Doppler), can extract target location

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Limitations of Angle of Arrival Estimation: The Cramer-Rao Bound

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Limitations of Angle of Arrival Estimation: Effect of Multipath Consider either a smooth surface or rough surface Specular surface results in two componentsdirect component and image component Rough surface results in both the above components as well as diffuse components Fading In extreme case, may result in signal cancellation Approach: Multi-taper Method

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Limitations in Angle of Arrival Estimation: Array-based Ambiguities Ambiguities can introduced to the estimation by the array itself Linear array has infinite ambiguities Planar array has two

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Limitations in Angle of Arrival Estimation: Atmospheric Turbulence Generally small (a few microradians) Can be significant depending on the application Guided missiles

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Estimation Algorithms Correlation Maximum Likelihood Estimation MUSIC: Multiple Signal Classification ESPIRIT: Estimation of Signal Parameters using Rotational Invariance Techniques Matrix Pencil

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Estimation Algorithms: Correlation

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Estimation Algorithms: Maximum Likelihood Estimation

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Estimation Algorithms: MUSIC

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Estimation Algorithms: Root-MUSIC

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Estimation Algorithm: ESPRIT

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Estimation Algorithms: Matrix Pencil

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Summary of Methods Discussed MUSIC/Root-MUSIC Requires assumption of N > M, resolving up to N-1 signals. Large number of signals ESPRIT Requires assumption that N > M as well Large number of signals Pencil Matrix Maximum value N/2 for even N, (N+1)/2 for odd Does not require large number of samples ½ time of Root-MUSIC, less computation If coherent detector is present, same accuracy as Root-MUSIC

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Passive Radar for Detection of Ground Moving Objects Recently developed for border security Utilizes AoA MUSIC technique alongside range-Doppler technique for target location Test operation at 1 GHz using a cell phone antenna emitting a BPSK signal

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Passive Radar for Detection of Ground Moving Objects

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References tionSecon06.pdf tionSecon06.pdf Combined Use of Various Passive Radar Techniques and Angle of Arrival using MUSIC for the Detection of Ground Moving Objects. Chan et al. p=&arnumber= p=&arnumber= Angle-of-Arrival of a Radar Beam in Atmospheric Turbulence. McMillan et al. p=&arnumber= p=&arnumber=999728

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