Journal article
Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences
Sruthy Skaria, Akram Al-Hourani, Robin J Evans, Kandeepan Sithamparanathan, Udaya Parampalli
Sensors | MDPI AG | Published : 2019
DOI: 10.3390/s19204459
Open access
Abstract
The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radar–radar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which en..
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Grants
Awarded by Australian Research Council Discovery Project Grant Cognitive Radars for Automobiles, ARC
Funding Acknowledgements
The research was supported by the Australian Research Council Discovery Project Grant Cognitive Radars for Automobiles, ARC grant number DP150104473.