Joint Temperature-Lasing Mode Compensation for Time-of-Flight LiDAR Sensors

We propose an expectation maximization (EM) strategy for improving the precision of time of flight (ToF) light detection and ranging (LiDAR) scanners. The novel algorithm statistically accounts not only for the bias induced by temperature changes in the laser diode, but also for the multi-modality o...

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Bibliographic Details
Published inSensors (Basel, Switzerland) Vol. 15; no. 12; pp. 31205 - 31223
Main Authors Alhashimi, Anas, Varagnolo, Damiano, Gustafsson, Thomas
Format Journal Article
LanguageEnglish
Published Switzerland MDPI 11.12.2015
MDPI AG
Subjects
Control Engineering
Gaussian mixture model (GMM)
LiDAR
maximum likelihood (ML)
mode hopping
multi-modality
Reglerteknik
SICK LMS200
ToF
SICK LMS200
maximum likelihood (ML)
LiDAR
EM
Gaussian mixture model (GMM)
multi-modality
ToF
mode hopping
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Summary:We propose an expectation maximization (EM) strategy for improving the precision of time of flight (ToF) light detection and ranging (LiDAR) scanners. The novel algorithm statistically accounts not only for the bias induced by temperature changes in the laser diode, but also for the multi-modality of the measurement noises that is induced by mode-hopping effects. Instrumental to the proposed EM algorithm, we also describe a general thermal dynamics model that can be learned either from just input-output data or from a combination of simple temperature experiments and information from the laser's datasheet. We test the strategy on a SICK LMS 200 device and improve its average absolute error by a factor of three.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s151229854