A New Model of Human Respiration for Algorithm Simulation Modeling in Radar Applications
K. Yu. Gavrilov, Timofey Shevgunov
Abstract
The paper aims at designing the advanced simulation model that is able to generate samples similar to human respiration signals typically acquired by a Doppler or Continuous-wave step frequency short-range radar system. The model is based on the continuous non-linear transformation of the mixture of a sine wave with amplitude and frequency modulation and a colored Gaussian noise. Despite not being based on a detailed physiological description of the respiration process, the proposed model can produce samples of respiration signals resembling the signals acquired by a radar with high accuracy. In contrast to the widely-used monoharmonic model, the model does not exhibit strict periodicity that allows researchers to consider it to be an appropriate sample generator for thorough testing procedures performed over existing algorithms of respiration signal detection as well as newly-created ones.