The extended differentiate and cross-multiply (DACM) algorithm fully recovered vibration patterns with measured noncalibrated amplitude agreeing well with known precalibrated data.
The extended DACM algorithm improves noise performance and allows direct retrieval of vibration amplitude without distance-dependent issues, with potential applications in vital sign detection.
Utilizing microwave continuous-wave Doppler radars to wirelessly detect mechanical vibrations have been attracting more and more interests in recent years. In this paper, aiming to solve the null point and nonlinear issues in small-angle approximation-based Doppler radar sensors and eliminate the codomain restriction in the arctangent demodulation approach, we propose and investigate an extended differentiate and cross-multiply (DACM) algorithm. With an additional accumulator, the noise performance of the original DACM algorithm is improved. Moreover, the amplitude information of the vibration can be directly retrieved from accumulation without involving any distance-dependent issue. Experimental validations show that the proposed algorithm can fully recover the vibration patterns with the measured noncalibrated amplitude agreeing well with the known precalibrated data. Application examples of mechanical fault detection and human vital sign detection are demonstrated, showing a wide range of potential applications of this algorithm.
Wang et al. (Wed,) reported a other. Extended differentiate and cross-multiply (DACM) algorithm was evaluated on Vibration pattern recovery and amplitude measurement. The extended differentiate and cross-multiply (DACM) algorithm fully recovered vibration patterns with measured noncalibrated amplitude agreeing well with known precalibrated data.
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