Statistical Models of RADAR and LIDAR Returns from Deer for Active Safety Systems 2016-01-0113
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.
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. Download Citation
Author(s):
William Buller, Rini Sherony, Brian Wilson, Michelle Wienert
Affiliated:
Michigan Technological University, TEMA
Pages: 5
Event:
SAE 2016 World Congress and Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Lidar
Statistical analysis
Radar
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