Optimal respiratory waveform selection based on range-multiple beams using a MIMO radar

WanHua Wu; Zhaocheng Yang

doi:10.1117/12.2631414

1 May 2022 Optimal respiratory waveform selection based on range-multiple beams using a MIMO radar

WanHua Wu, Zhaocheng Yang

Author Affiliations +

Proceedings Volume 12171, Thirteenth International Conference on Signal Processing Systems (ICSPS 2021); 1217106 (2022) https://doi.org/10.1117/12.2631414
Event: Thirteenth International Conference on Signal Processing Systems (ICSPS 2021), 2021, Shanghai, China

Abstract

In this paper, we propose an optimal respiratory waveform selection algorithm based on range-multiple beams using a 77GHz frequency modulated continuous wave (FMCW) multiple-input-multiple-output (MIMO) radar. Generally speaking, the human chest is a multi-scattering target and the optimal monitoring position changes in a small range during breathing movement. According to this motion feature, we roughly locate the target in the range-angle candidate box based on range fast Fourier transform (FFT) and Capon direction of arrival (DOA) algorithm, respectively. Additionally, the fixed beamforming is utilized to algin the detected target site which can reduce the interference of clutter and enhance the signal-to-noise ratio (SNR). Then, the extended differential and cross-multiply (DACM) algorithm is further applied for phase unwrapping and the optimal respiratory waveform is extracted based on the features of respiratory periodicity. Ultimately, the respiratory rate is estimated by the frequency-time phase regression (FTPR) algorithm. Experiments with and without interference are conducted and the results show that the proposed algorithm can obtain accurate respiratory rate with mean square errors (MSE) 0.6862 breath²/min compared with the reference vital signs data.

Citation Download Citation

WanHua Wu and Zhaocheng Yang "Optimal respiratory waveform selection based on range-multiple beams using a MIMO radar", Proc. SPIE 12171, Thirteenth International Conference on Signal Processing Systems (ICSPS 2021), 1217106 (1 May 2022); https://doi.org/10.1117/12.2631414

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