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Using FMCW in Autonomous Cars to Accurately Estimate the Distance of the Preceding Vehicle

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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.

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Acknowledgements

The authors would like to thank the ministry of science and technology, Taiwan, for financially supporting this research grant No.MOST109-2222-E-018-001-MY2.

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Correspondence to Shih-Lin Lin.

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Hsu, WT., Lin, SL. Using FMCW in Autonomous Cars to Accurately Estimate the Distance of the Preceding Vehicle. Int.J Automot. Technol. 23, 1755–1762 (2022). https://doi.org/10.1007/s12239-022-0153-4

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  • DOI: https://doi.org/10.1007/s12239-022-0153-4

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