Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions

Automotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001). Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar senso...

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Main Authors: R. H. Rasshofer, K. Gresser
Format: Article
Language:deu
Published: Copernicus Publications 2005-01-01
Series:Advances in Radio Science
Online Access:http://www.adv-radio-sci.net/3/205/2005/ars-3-205-2005.pdf
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spelling doaj-f069bfe711564a76a866ca99cac40d9b2020-11-25T01:30:07ZdeuCopernicus PublicationsAdvances in Radio Science 1684-99651684-99732005-01-013205209Automotive Radar and Lidar Systems for Next Generation Driver Assistance FunctionsR. H. RasshoferK. GresserAutomotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001). Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar sensors available on the market today suffer from low angular resolution and poor target detection in medium ranges (30 to 60m) over azimuth angles larger than &#x00B1;30°. In contrast, Lidar sensors show large sensitivity towards environmental influences (e.g. snow, fog, dirt). Both sensor technologies today have a rather high cost level, forbidding their wide-spread usage on mass markets. </p><p style=&quot;line-height: 20px;&quot;> A common approach to overcome individual sensor drawbacks is the employment of data fusion techniques (Bar-Shalom, 2001). Raw data fusion requires a common, standardized data interface to easily integrate a variety of asynchronous sensor data into a fusion network. Moreover, next generation sensors should be able to dynamically adopt to new situations and should have the ability to work in cooperative sensor environments. </p><p style=&quot;line-height: 20px;&quot;> As vehicular function development today is being shifted more and more towards virtual prototyping, mathematical sensor models should be available. These models should take into account the sensor&apos;s functional principle as well as all typical measurement errors generated by the sensor.http://www.adv-radio-sci.net/3/205/2005/ars-3-205-2005.pdf
collection DOAJ
language deu
format Article
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author R. H. Rasshofer
K. Gresser
spellingShingle R. H. Rasshofer
K. Gresser
Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions
Advances in Radio Science
author_facet R. H. Rasshofer
K. Gresser
author_sort R. H. Rasshofer
title Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions
title_short Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions
title_full Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions
title_fullStr Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions
title_full_unstemmed Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions
title_sort automotive radar and lidar systems for next generation driver assistance functions
publisher Copernicus Publications
series Advances in Radio Science
issn 1684-9965
1684-9973
publishDate 2005-01-01
description Automotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001). Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar sensors available on the market today suffer from low angular resolution and poor target detection in medium ranges (30 to 60m) over azimuth angles larger than &#x00B1;30°. In contrast, Lidar sensors show large sensitivity towards environmental influences (e.g. snow, fog, dirt). Both sensor technologies today have a rather high cost level, forbidding their wide-spread usage on mass markets. </p><p style=&quot;line-height: 20px;&quot;> A common approach to overcome individual sensor drawbacks is the employment of data fusion techniques (Bar-Shalom, 2001). Raw data fusion requires a common, standardized data interface to easily integrate a variety of asynchronous sensor data into a fusion network. Moreover, next generation sensors should be able to dynamically adopt to new situations and should have the ability to work in cooperative sensor environments. </p><p style=&quot;line-height: 20px;&quot;> As vehicular function development today is being shifted more and more towards virtual prototyping, mathematical sensor models should be available. These models should take into account the sensor&apos;s functional principle as well as all typical measurement errors generated by the sensor.
url http://www.adv-radio-sci.net/3/205/2005/ars-3-205-2005.pdf
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