Statistical Models of RADAR and LIDAR Returns from Deer for Active Safety Systems

Paper #:
  • 2016-01-0113

Published:
  • 2016-04-05
Citation:
Buller, W., Sherony, R., Wilson, B., and Wienert, M., "Statistical Models of RADAR and LIDAR Returns from Deer for Active Safety Systems," SAE Technical Paper 2016-01-0113, 2016, https://doi.org/10.4271/2016-01-0113.
Pages:
5
Abstract:
Based on RADAR and LiDAR measurements of deer with RADAR and LiDAR in the Spring and Fall of 2014 [1], we report the best fit statistical models. The statistical models are each based on time-constrained measurement windows, termed test-points. Details of the collection method were presented at the SAE World Congress in 2015. Evaluation of the fitness of various statistical models to the measured data show that the LiDAR intensity of reflections from deer are best estimated by the extreme value distribution, while the RCS is best estimated by the log-normal distribution. The value of the normalized intensity of the LiDAR ranges from 0.3 to 1.0, with an expected value near 0.7. The radar cross-section (RCS) varies from -40 to +10 dBsm, with an expected value near -14 dBsm.
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