Detection of a Living Person With Unknown Reflection and Respiration Using MIMO Radar

Consider the presence of a human body, which could possibly be fake/dead, in the area under monitoring. The purpose of this paper is to determine whether the human body is a living person or not, using multiple-input multiple-output (MIMO) radar. Taking into account the oscillatory characteristics of human respiration, the MIMO radar received signal model for a living person is developed, assuming that the chest displacement, respiration frequency, and reflection coefficients are deterministic but unknown. The living person detection problem can be formulated as a binary composite hypothesis testing, for which the generalized likelihood ratio test (GLRT)-based detector is derived. Further consider that the human respiration could be very weak, making the two hypotheses too close to be well distinguished. Tailored for deciding between two close hypotheses with unknown parameters, the generalized locally most powerful test (GLMPT) for MIMO radar living person detection is proposed. Theoretical performance analyses are provided for both the GLRT-based and GLMPT-based MIMO radar living person detectors. The closed-form expressions for the detection and false alarm probabilities of the GLMPT-based detector are derived for a given respiration frequency. Numerical examples are presented to evaluate the performance of the GLRT and GLMPT-based detectors in detecting living persons with weak respiration. The impacts of system parameters on detector performance are investigated.