USING FMCW IN AUTONOMOUS CARS TO ACCURATELY ESTIMATE
THE DISTANCE OF THE PRECEDING VEHICLE |
Wei-Tai Hsu 1, Shih-Lin Lin 2 |
1Department of Electrical Engineering, Zhaoqing University 2Graduate Institute of Vehicle Engineering, National Changhua University of Education |
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ABSTRACT |
Failure to maintain a safe driving distance between moving vehicles is one of the major causes of traffic
accidents. Research on maintaining a safe distance with autonomous vehicles is especially important. This paper uses the
Hilbert-Huang transform (HHT) method and error estimation to analyze the frequency modulated continuous wave (FCMW)
signal of Doppler radar for autonomous vehicle applications. The FMCW signal is decomposed into intrinsic mode functions
(IMF) using the empirical mode decomposition (EMD) method. The Doppler radar signal is then reproduced through the
Hilbert spectrum obtained using the instantaneous amplitude and instantaneous frequency. The characteristics of the motion
of the object are obtained by analyzing the reconstructed Doppler radar signal. The simulation and verification results confirm
that this method can accurately estimate the distance between vehicles within the range of 20 ~ 120 meters at speeds of 50 ~
230 km/h. Error estimation is also obtained based on the distance to the car in front and the vehicle’s speed. This study
contributes by the application of the proposed Hilbert-Huang transform (HHT) method for the analysis of the frequency
modulated continuous wave (FCMW) signal of Doppler radars. The method of this study has been applied to multi-target
detection. In this simulation, there are 5 targets, each with a different distance from the car and the speed of the car. The
simulation results show that the proposed method can improve the accuracy of the sensor in terms of estimating the distance,
reliability and stability of the vehicle, and can increase the safety of the autonomous vehicles. |
Key Words:
Autonomous car, FMCW, HHT, Automotive radar |
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