A Modulated Approach for Improving MFSK RADARS to Resolve Mutual Interference on Autonomous Vehicles (AVs)

Area of Science:

• Electrical Engineering
• Signal Processing
• Automotive Technology

Background:

• Automotive radar systems face challenges with mutual interference in a dense signal environment.
• Existing radar waveforms may not efficiently support the simultaneous detection of multiple static and moving targets.

Purpose of the Study:

• To propose and evaluate a novel automotive radar waveform based on M-ary frequency shift key (MFSK) principles.
• To address mutual interference issues in automotive radar frequency bands using advanced coding schemes.
• To enhance Doppler estimation and simultaneous range detection capabilities for autonomous vehicles (AVs).

Main Methods:

• Development of a novel MFSK-based automotive radar waveform operating between 76-81 GHz with 1 GHz steps.
• Implementation of a triangular chirp sequence for improved target detection.
• Evaluation of binary and combined transform coding schemes for unique signal generation and correlation.

Main Results:

• The proposed triangular chirp MFSK waveform demonstrates potential for improved Doppler estimation.
• Coding schemes effectively provide unique signals, mitigating mutual interference in dense AV environments.
• Experimental data and comparisons show the efficacy of the modulated frequencies compared to other systems.

Conclusions:

• The novel MFSK automotive radar waveform with advanced coding offers a promising solution for enhanced target detection and interference mitigation.
• This approach can significantly improve the performance and reliability of autonomous vehicle perception systems.