Real-time identification of aircraft sound events.

Metropolitan airports constitute an environmental nuisance, mainly due to noise pollution originating from aircraft landings and takeoffs, affecting the wellbeing of the airports' neighboring populations. Noise measurement is considered the fundamental means to evaluate, enforce, validate, and control noise abatement. Noise measurements performed by sound monitors located close to urban airports are often disrupted by urban background noise that interferes with aircraft sounds. Detecting aircraft noise, classifying, identifying, and separating it from the residual background noise is a challenge for unattended aircraft noise monitors. This paper suggests a simple and inexpensive methodology, based on ADS-B (Automatic Dependent Surveillance-Broadcast), which can facilitate isolating aircraft noise from background noise. Experiments showed that using ADS-B driven noise monitors is at least as accurate as the commonly used radar-driven noise monitors, in terms of true positive, false positive, or false negative detection during the examined periods.