Abstract
Specialized rescuer radars, employed for detecting living individuals during rescue operations amid natural or man-made disasters, operate by estimating the nonstationary spectral characteristics of reflected signals induced by breathing and heartbeats. The nonstationary spectra resulting from Doppler phase shifts in reflected radar signals are attributed to the breathing and heartbeat processes of living humans. These phase fluctuations occur at ultra-low frequencies and can be effectively detected using extended pseudo-noise probing signals, such as those based on Mersenne codes. The method for tracking the power spectrum of a process, where the rates of change in the correlation function at various lags differ over time, is presented. The method is discussed in terms of its application with finite-length correlation processes. It allocates a short memory for rapidly varying terms in the correlation while concurrently employing longer-term averaging for the more stationary terms. Time-varying spectral estimates of rescuer radar signals are derived through the processing of resulting correlation estimates of signals reflected from a living human body. Examples of real spectrum estimates are provided to illustrate that improved tracking can be achieved compared to employing a constant lag-invariant averaging method.
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