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Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences.

Sruthy Skaria1, Akram Al-Hourani2, Robin J Evans3

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Summary
This summary is machine-generated.

Wireless sensor interference is a growing challenge. This study introduces a novel method using pseudo-random cyclic orthogonal sequences (PRCOS) to significantly reduce automotive radar interference, enhancing sensing performance.

Keywords:
automotive radarinterference mitigationsequence designstepped frequency radar

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Wireless Communication

Background:

  • Increasing density of wireless sensors sharing the electromagnetic spectrum presents significant interference challenges.
  • Automotive radars are a key sensor type susceptible to interference, impacting sensing performance.

Purpose of the Study:

  • To investigate interference mechanisms in automotive radars.
  • To evaluate the impact of radar waveform design and receiver processing on interference.
  • To propose and validate a novel interference mitigation technique.

Main Methods:

  • Analysis of interference statistics based on radar waveform design and receiver processing.
  • Development of a novel interference mitigation approach using pseudo-random cyclic orthogonal sequences (PRCOS).
  • Benchmarking PRCOS against random stepped frequency waveform sequences (RSFWS) using simulations and analytical methods.
  • Experimental validation on commercial automotive radars.

Main Results:

  • PRCOS enables rapid learning of the interference environment and avoidance of frequency overlap.
  • Significant interference mitigation is achieved with PRCOS, offering analytically tractable statistical characterization.
  • Simulations and analytical results demonstrate considerable interference reduction compared to RSFWS.
  • Experimental measurements confirm the effectiveness of the proposed model and framework.

Conclusions:

  • The proposed PRCOS approach offers a robust solution for mitigating radar-radar interference in dense wireless sensor environments.
  • This method significantly improves automotive radar sensing performance by reducing interference.
  • The findings are applicable to a broader range of sensor systems facing similar interference issues.