Optical simulation of time-of-flight sensor accuracy in rain

Baumgart, Marcus; Consani, Cristina; Dielacher, Markus; Druml, Norbert

doi:10.1109/cleoe-eqec.2017.8086908

“…The transmission and reflection in two different positions were investigated. In [26] the influence of weather effects, in particular rain droplets, on distance and depth measurements obtained with a ToF camera-based sensor are examined based on optical simulation models in 2017. Trierweiler et al from Robert Bosch obtained an almost-homogeneous distribution of dust on polycarbonate sheets resulting in a maximal range decrement of 25% in [27].…”

Section: B Related Workmentioning

confidence: 99%

Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems

Liu¹,

Conde²

2022

Preprint

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In the past few years, 3D imaging technology has received a lot of attention. Time-of-Flight (ToF) cameras based on the indirect ToF principle calculate depth information by measuring the phase shift between the emitted periodic signal and the reflected signal. In this work, we aim to study the effect of dirt on 3D imaging systems quantitatively. To this end, ten sheets with different transmittances, between 50% and 100% are used. To the best of our knowledge, for the first time we provide standardized methods for evaluating the effect of dirt on protective covers in the depth estimation of ``flash lidar''. The experiments have shown that the depth measurements obtained using the multi-frequency estimation method are more accurate in the presence of dust than the single-frequency estimation method.

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“…The transmission and reflection in two different positions were investigated. In [32] the influence of weather effects, in particular rain droplets, on distance and depth measurements obtained with a ToF camera-based sensor are examined based on optical simulation models in 2017. Trierweiler et al from Robert Bosch obtained an almost-homogeneous distribution of dust on polycarbonate sheets resulting in a maximal range decrement of 25% in [33].…”

Section: B Related Workmentioning

confidence: 99%

Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems

Liu

¹

,

Conde

²

2022

IEEE Sensors J.

1

0

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In the past few years, 3D imaging technology has received a lot of attention. Time-of-Flight (ToF) cameras based on the indirect ToF principle calculate depth information by measuring the phase shift between the emitted periodic signal and the reflected signal. When the illumination from the modulated light source reaches the same pixel through multiple paths, multipath interference will occur. Acquisitions at multiple modulation frequencies are then required to separate the interfering paths. Parametric spectral estimation methods, such as Prony's method and its robust variants, have shown success in resolving multiple paths from multi-frequency measurements. With the widespread usage of ToF cameras in various fields, the operating environment of the camera should be taken into account in order to obtain accurate 3D images.In this work, we aim to study the effect of dirt on 3D imaging systems quantitatively. To this end, ten sheets with different transmittances, between 50% and 100% are used. To the best of our knowledge, for the first time we provide standardized methods for evaluating the effect of dirt on protective covers in the depth estimation of "flash lidar". The accuracy of depth measurements obtained by multi-frequency multipath recovery in the absence of dust is up to 99%. However, when the light transmittance of the protective cover is less than 90%, the measurement result is already unreliable. The experiments have shown that the depth measurements obtained using the multi-frequency estimation method are more accurate in the presence of dust than the single-frequency estimation method.

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“…3) Environmental Interference: Some publications exist that study the influence of the weather and dirt on sensors. In [20] the influence of weather effects, in particular rain droplets, on distance and depth measurements obtained with a ToF camera-based sensor are examined based on optical simulation models. A ToF LiDAR operating within a foggy environment is presented in [21], where performance is qualitatively and quantitatively investigated.…”

Section: A Related Workmentioning

confidence: 99%

Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems

Liu¹,

Conde²

2022

Preprint

0

View full text Add to dashboard Cite

In the past few years, 3D imaging technology has received a lot of attention. Time-of-Flight (ToF) cameras based on the indirect ToF principle calculate depth information by measuring the phase shift between the emitted periodic signal and the reflected signal. In this work, we aim to study the effect of dirt on 3D imaging systems quantitatively. To this end, ten sheets with different transmittances, between 50% and 100% are used. To the best of our knowledge, for the first time we provide standardized methods for evaluating the effect of dirt on protective covers in the depth estimation of ``flash lidar''. The experiments have shown that the depth measurements obtained using the multi-frequency estimation method are more accurate in the presence of dust than the single-frequency estimation method.

show abstract

Optical simulation of time-of-flight sensor accuracy in rain

Cited by 6 publications

References 3 publications

Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems

Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems

Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems

Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems

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