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    Signal interactions between lidar scanners

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    POPKO-THESIS-2019.pdf (8.835Mb)
    Date
    2019-04-10
    Author
    Popko, Gerald B.
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    Abstract
    Light detection and ranging (lidar) is used for obtaining precision spatial data to aid autonomous vehicle navigation. However, little published work exists regarding signal interference between lidar devices. Lidar signal interference is the undesired reception of signal energy that may compromise the accuracy of spatial data. A theory of lidar interference is presented which characterizes two types of interference – direct and scattered interference. Direct interference results from the direct coupling of light from a second lidar into the lidar’s receiver. Scattered interference results from the detection of another lidar’s light scattered from a target. Both can result in erroneous ranging data. A mathematical model is presented that describes the limits and occurrences of scattered interference. The upper limit of scattered interference is the fraction of beam intersection time between two lidar scanners and shown to have a minimum and maximum value of 0 and 1/2, respectively, with most scanner arrangements converging to 1/4. The concept of intersection point density is introduced from the locus of the beams’ intersection points and shown to be a predictor of scattered interference. Five test case experiments were conducted that demonstrated the occurrence of lidar interference. Angularly, direct interference is shown to be categorized by a higher occurrence of out-of-tolerance points while scattered interference results in larger average of ranging errors. A Monte Carlo simulation is presented that models the interference between two lidars using the proposed theory. A comparison of the simulated and experimental results demonstrates the theory’s general explanation of lidar interference occurrences, while further refinement may be found from radiometric considerations.
    URI
    http://hdl.handle.net/1853/62690
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    • Georgia Tech Theses and Dissertations [23878]
    • School of Electrical and Computer Engineering Theses and Dissertations [3381]

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