Human presence detection using a particle filter on ultrasonic micro-Doppler measurements for assisting rescue work in large buildings

Abstract

When the re brigade arrives at a burning building, it is of vital importance that people who are still inside can quickly be found. In this thesis we contribute to an ultrasonic sound sensor for human presence detection in smoke-lled spaces. This type of sensor could assist the re brigade when evacuating a large building by directing them to the places where their help is most needed. The advantage of ultrasonic sound over other sensors or cameras is that its signal is able to pierce through smoke, does not require badges or other wearable devices and introduces little privacy and security risks. In addition, ultrasonic sensors are very inexpensive making it possible to equip every room of a building with an ultrasonic presence detector. In this research an ultrasonic sensor was built for less than 20 Euros and it was found to be unaected by the glycerine based smoke that it was tested in. Using a particle filter based on sequential importance resampling as well as a Filter based on Gaussian approximation of the posterior density the resulting system was reliably able to detect when there was a single person walking in the sensor direction, even when other sources of movement such as doors and chairs were present.