Deep learning-based indoor distance estimation scheme using FMCW radar

13Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

In the distance estimation scheme using Frequency-Modulated-Continuous-Wave (FMCW) radar, the frequency difference, which was caused by the time delay of the received signal reflected from the target, is calculated to estimate the distance information of the target. In this pa-per, we propose a distance estimation scheme exploiting the deep learning technology of artificial neural network to improve the accuracy of distance estimation over the conventional Fast Fourier Transform (FFT) Max value index-based distance estimation scheme. The performance of the proposed scheme is compared with that of the conventional scheme through the experiments evaluating the accuracy of distance estimation. The average estimated distance error of the proposed scheme was 0.069 m, while that of the conventional scheme was 1.9 m.

Cite

CITATION STYLE

APA

Park, K. E., Lee, J. P., & Kim, Y. (2021). Deep learning-based indoor distance estimation scheme using FMCW radar. Information (Switzerland), 12(2), 1–14. https://doi.org/10.3390/info12020080

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free