Abstract:Abstract-Acoustic localization by means of sensor arrays has a variety of applications, from conference telephony to environment monitoring. Many of these tasks are appealing for implementation on embedded systems, however large dataflows and computational complexity of multi-channel signal processing impede the development of such systems. This paper proposes a method of acoustic localization targeted for distributed systems, such as Wireless Sensor Networks (WSN). The method builds on an optimized localizati… Show more
“…To overcome problems associated with communicating signal frames we apply a simplified localization approach of Initial Search Region Reduction (ISRR), recently developed by our research team [1]. The main idea behind ISRR lies in maximally confining the region of acoustic source disposition as a preliminary procedure to SRP-PHAT or other localization method [6]. Having already established that SRP-PHAT requires raw information from all sensors in the network, we do not apply it for this specific ISR system configuration.…”
This paper considers an autonomous ground Intelligence, Surveillance and Reconnaissance (ISR) system comprising of multiple distributed, wirelessly communicating smart sensors. The ISR system, in turn, is a part of a larger System of Systems (SoS) consisting of aerial, manned, etc. surveillance systems and information collection centers. The smart sensors of the ISR system perform environment monitoring using different modalities and exchange object detection and identification results to assess the situation and provide other SoS components with this information. In the paper we discuss using acoustic, magnetic and Passive Infrared (PIR) sensor information for target detection and identification. We also propose an approach of distributed acoustic source localization and a method of velocity estimation using PIR data. For sensor communication an asynchronous adhoc WSN configuration is proposed. The system is implemented on low power smart sensors utilizing Atmel ATmega128RFA1 processors with integrated 2.4GHz IEEE 802.15.4 compliant radio transceivers.
“…To overcome problems associated with communicating signal frames we apply a simplified localization approach of Initial Search Region Reduction (ISRR), recently developed by our research team [1]. The main idea behind ISRR lies in maximally confining the region of acoustic source disposition as a preliminary procedure to SRP-PHAT or other localization method [6]. Having already established that SRP-PHAT requires raw information from all sensors in the network, we do not apply it for this specific ISR system configuration.…”
This paper considers an autonomous ground Intelligence, Surveillance and Reconnaissance (ISR) system comprising of multiple distributed, wirelessly communicating smart sensors. The ISR system, in turn, is a part of a larger System of Systems (SoS) consisting of aerial, manned, etc. surveillance systems and information collection centers. The smart sensors of the ISR system perform environment monitoring using different modalities and exchange object detection and identification results to assess the situation and provide other SoS components with this information. In the paper we discuss using acoustic, magnetic and Passive Infrared (PIR) sensor information for target detection and identification. We also propose an approach of distributed acoustic source localization and a method of velocity estimation using PIR data. For sensor communication an asynchronous adhoc WSN configuration is proposed. The system is implemented on low power smart sensors utilizing Atmel ATmega128RFA1 processors with integrated 2.4GHz IEEE 802.15.4 compliant radio transceivers.
“…In this case in the scope of this thesis the collection of receivers is called not an array, but a distributed sensor network. Sensor networks were investigated by Astapov et al (2015). When a set of distributed receiver arrays are used instead of singular microphones, a configuration is called distributed sensor array.…”
Section: Acoustic Scenarios Of Sound Source Localizationmentioning
“…Since SRP approaches are based on the exploitation of TDOA information, synchronization issues also arise when applying SRP in WASNs. As in the case of source localization using DOAs or TDOAs, SRP-based approaches for WASNs have been proposed considering that multiple microphones are available at each node [89][90][91]. In these cases, the SRP method can be used for acquiring DOA estimates at each node or collecting source location estimates that are merged by a central node.…”
Wireless acoustic sensor networks (WASNs) are formed by a distributed group of acoustic-sensing devices featuring audio playing and recording capabilities. Current mobile computing platforms offer great possibilities for the design of audio-related applications involving acoustic-sensing nodes. In this context, acoustic source localization is one of the application domains that have attracted the most attention of the research community along the last decades. In general terms, the localization of acoustic sources can be achieved by studying energy and temporal and/or directional features from the incoming sound at different microphones and using a suitable model that relates those features with the spatial location of the source (or sources) of interest. This paper reviews common approaches for source localization in WASNs that are focused on different types of acoustic features, namely, the energy of the incoming signals, their time of arrival (TOA) or time difference of arrival (TDOA), the direction of arrival (DOA), and the steered response power (SRP) resulting from combining multiple microphone signals. Additionally, we discuss methods not only aimed at localizing acoustic sources but also designed to locate the nodes themselves in the network. Finally, we discuss current challenges and frontiers in this field.
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