A 3D acoustic vector sensor based on MEMS microphones and its application to road traffic monitoring is presented in the paper. The sensor is constructed from three pairs of digital MEMS microphones, mounted on the orthogonal axes. Signals obtained from the microphones are used to compute sound intensity vectors in each direction. With this data, it is possible to compute the horizontal and vertical angle of an incoming sound....

This work describes the system and methods of data analysis we use for beehive monitoring. We present overview of the hardware infrastructures used in hive monitoring systems and we describe algorithms used for analysis of this kind of data. Based on acquisited signals we construct the application that is capable to detect an absence of honey bee queen. We describe our method of signal analysis and present results that allow us...

This paper presents a method for the joint detection and direction of arrival (DOA) estimation of low probability of detection (LPD) signals. The proposed approach is based on using the antenna array to receive spread-spectrum signals hidden below the noise floor. Array processing exploits the spatial correlation between phase-delayed copies of the signal and allows us to evaluate the parameter used to make the decision about the...

Praca zawiera szczegółowy opis metodyki prowadzenia obliczeń i ekspozycji wyników przewidywanych warunków detekcji systemów hydroakustycznych w zestawie pomiarowym rozkładów prędkości dźwięku. Podstawa obliczeń są zamierzone rozkłady wartości prędkości propagacji dźwięku w funkcji głębokości akwenu a metodyka polega na kojarzeniu wyliczonego metodą gęstości promieni rozkładu natężenia fali akustycznej w pionowym przekroju akwenu...

An evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...