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arXiv 1908.04417eess.SPeess.IV
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Low-cost low-power in-vehicle occupant detection with mm-wave FMCW radar

Mostafa Alizadeh, Hajar Abedi, George Shaker

英文摘要:

In this paper, we use a low-cost low-power mm-wave frequency modulated continuous wave (FMCW) radar for the in-vehicle occupant detection. We propose an algorithm using Capon filter for the joint range-azimuth estimation. Then, the minimum necessary features are extracted to train machine learning classifiers to have reasonable computational complexity while achieving high accuracy. In addition, experiments were carried out in a minivan to detect occupancy of each row using support vector machine (SVM). Finally, our proposed system achieved 97.8% accuracy on average in finding the defined scenarios. Moreover, the system can correctly identify if the vehicle is occupied or not with 100% accuracy.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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