Automotive Radar Interference Mitigation with Fast-Time-Frequency Mode Retrieval

Jin, Sian; Wang, Pu; Boufounos, Petros T.; Orlik, Phil; Roy, Sumit

doi:10.1109/radarconf2248738.2022.9764338

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…1) Fast-time (range) domain: interference-zeroing [16]- [18], sparse reconstruction [19], [20], adaptive noise cancellers [21], signal separation [22], fast-time-frequency mode retrieval [23], and fast-time neural networks [24], [25]; 2) Slow-time (Doppler) domain: waveform randomization [26], [27], ramp filtering [28], and slow-time neural network [29]; 3) Joint range-Doppler domain: neural network based de-noisers [30]- [33]; 4) Communication-assisted scheduling, such as timedivision multiple access [34], and chirp slope and frequency offset scheduling [35].…”

Section: Introductionmentioning

confidence: 99%

Spatial-Domain Interference Mitigation for Slow-Time MIMO-FMCW Automotive Radar

Jin

Wang

Boufounos

et al. 2022

2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM)

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This paper considers mutual interference mitigation among automotive radars using frequency-modulated continuous wave (FMCW) signal and multiple-input multiple-output (MIMO) virtual arrays. For the first time, we derive a general interference signal model that fully accounts for not only the time-frequency incoherence, e.g., different FMCW configuration parameters and time offsets, but also the slow-time code MIMO incoherence and array configuration differences between the victim and interfering radars. Along with a standard MIMO-FMCW object signal model, we turn the interference mitigation into a spatial-domain object detection under incoherent MIMO-FMCW interference described by the explicit interference signal model, and propose a constant false alarm rate (CFAR) detector. More specifically, the proposed detector exploits the structural property of the derived interference model at both transmit and receive steering vector space. We also derive analytical closedform expressions for probabilities of detection and false alarm. Performance evaluation using both synthetic-level and phased array system-level simulation confirms the effectiveness of our proposed detector over selected baseline methods.

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