A sleep monitor employing non-intrusive radar technology and machine learning can provide automatic sleep stage classification in healthy subjects. Polysomnography (PSG) is the medical gold standard for objective sleep measurements. The present study validates a non-contact sleep sensor using radar technology and machine learning against PSG. The results show that the monitor can provide automatic sleep stage classification with a precision close to PSG in a sample of healthy, mostly young subjects.