Real-Time Aircraft Noise Detection Based on Large-Scale Noise Data

With the development of Internet of Things, aircraft noise monitoring system can be more accurate and real-time by laying large-scale monitoring devices on monitoring areas. In this paper, we present a real-time aircraft noise detection algorithm based on large-scale noise data. The spatial characteristics of the distribution of noises are discussed firstly as the premise of analyzing the differences of aircraft noises and other kinds of noises. Then we propose a way to represent the tendency surface of noise propagation and attenuation, and the unit tendency increment in one direction is defined. Finally the aircraft noise is detected by comparing threshold with the maximum sum of tendencies that all points direct to the estimated aircraft position. The noise data of the experiment is got by the monitors lay around a large domestic airport and the experiment shows that the algorithm can detect aircraft even it is 1000m away from the monitoring area and the trace of the aircraft can be reappeared roughly.