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Low-Complexity-Based RD-MUSIC with Extrapolation for Joint TOA and DOA at Automotive FMCW Radar Systems

Title
Low-Complexity-Based RD-MUSIC with Extrapolation for Joint TOA and DOA at Automotive FMCW Radar Systems
Authors
Kim, SangdongKim, BongseokLee, Jonghun
DGIST Authors
Kim, Sangdong; Kim, Bongseok; Lee, Jonghun
Issue Date
2020-06
Citation
Journal of Sensors, 2020, 7342385
Type
Article
Article Type
Article
ISSN
1687-725X
Abstract
Low-complexity-based reduced-dimension-multiple-signal classification (RD-MUSIC) is proposed with extrapolation for joint time delay of arrivals (TOA) and direction of arrivals (DOA) at automotive frequency-modulated continuous-wave (FMCW) radar systems. When a vehicle is driving on the road, the automotive FMCW radar can estimate the position of multiple other vehicles, because it can estimate multiple parameters, such as TOA and DOA. Over time, the requirement of the accuracy and resolution parameters of automotive FMCW radar is increasing. To accurately estimate the parameters of multiple vehicles, such as range and angle, it is difficult to use a low-resolution algorithm, such as the two-dimensional fast Fourier transform. To improve parameter estimation performance, high-resolution algorithms, such as the 2D-MUSIC, are required. However, the conventional high-resolution methods have a high complexity and, thus, are not applicable to a real-time radar system for a vehicle. Therefore, in this work, a low-complexity RD-MUSIC with extrapolation algorithm is proposed to have a resolution similar to that of a high-resolution algorithm to estimate the position of other vehicles. Compared with conventional low complexity high resolution, in experimental results, the proposed method had better performance. © 2020 Sangdong Kim et al.
URI
http://hdl.handle.net/20.500.11750/12543
DOI
10.1155/2020/7342385
Publisher
Hindawi Limited
Related Researcher
Files:
Collection:
Division of Automotive Technology1. Journal Articles


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