Premium
Downscaling method of target geometries with minimum distortions on statistical features of radar cross sections for 77‐GHz automotive radars
Author(s) -
Lee D.,
Byun G.,
Kim H.,
Choo H.,
Park J.E.
Publication year - 2017
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.30652
Subject(s) - radar cross section , radar , distortion (music) , cumulative distribution function , downscaling , cross section (physics) , scale factor (cosmology) , automotive industry , acoustics , computer science , algorithm , remote sensing , mathematics , engineering , physics , electronic engineering , statistics , geology , aerospace engineering , probability density function , meteorology , telecommunications , cmos , amplifier , metric expansion of space , dark energy , cosmology , quantum mechanics , precipitation
This article proposes a downscaling method of radar targets using the Kolmogorov‐Smirnov (K‐S) test to reduce the computational load of the radar cross section (RCS) simulation for 77‐GHz automotive radars. The proposed method is employed to various target geometries, whose shapes are determined by the geometrical factor (GF), and their sizes are adjusted using a linear scale factor (SF). For each target geometry, the cumulative distribution function (CDF) is calculated by using the RCSs that are obtained from various observation angles and frequency points. Then, the K‐S test is applied for the CDF to investigate a proper scaling factor that maintains the K‐S test value of less than 0.1. The proposed method is also extended to a commercial vehicle to further verify the feasibility, and the results show that the geometries of hexahedrons and the vehicle can be downscaled by the factors of 0.6 and 0.8, respectively, without a significant distortion on the statistical features.