Completed

Automotive Radar Interference Mitigation

Adaptive noise canceller for FMCW radar to improve SIR and reduce ghost targets

Overview

Interference among frequency modulated continuous wave (FMCW) automotive radars can either increase the noise floor, which occurs in most cases, or generate a ghost target in rare situations. To address the increment of noise floor due to interference, we proposed a low calculation cost method using adaptive noise canceller to increase the signal-to-interference ratio (SIR). Both simulation and experimental results showed good interference mitigation performance, making automotive radar systems more reliable in dense traffic scenarios.

Key Highlights

Automotive Radar
Interference Mitigation
Adaptive Noise Canceller
SIR Improvement
Ghost Target Reduction

Methodology

Adaptive noise cancellation pipeline for interference suppression and ghost target reduction. Low computational cost approach suitable for real-time automotive applications.

Technologies

FMCW Radar Adaptive Filtering Signal Processing SVM Classification Interference Detection

Project Details

Start Date: June 2017
End Date: April 2019
Status: Completed

Resources

Related Publications

Automotive Radar Interference Mitigation using Adaptive Noise Canceller

F. Jin, S. Cao

IEEE Transactions on Vehicular Technology, 2019

View Paper

Support Vector Machines for Classification of Automotive Radar Interference

R. Zhang, S. Cao

IEEE Radar Conference, 2018

View Paper

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