Direction of Arrival Estimation and Localization Using Acoustic Sensor Arrays

Kunin, V. N.; Turqueti, Marcos; Saniie, Jafar; Oruklu, Erdal

doi:10.4236/jst.2011.13010

Cited by 17 publications

(7 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Assuming that sound velocity c = 340 m·s −1 , t 12 is the arriving time difference between S 1 and S 2 , s , and t 23 is the arriving time difference between S 2 and S 3 , s . Time delay is automatically computed by Kinect adaptive methods embedded in the LabVIEW software and can be found from the triangle cosine theorem [ 25 ]:

…”

Section: Methodsmentioning

confidence: 99%

A Sound Source Localisation Analytical Method for Monitoring the Abnormal Night Vocalisations of Poultry

Lao

Teng

2018

Sensors

View full text Add to dashboard Cite

Due to the increasing scale of farms, it is increasingly difficult for farmers to monitor their animals in an automated way. Because of this problem, we focused on a sound technique to monitor laying hens. Sound analysis has become an important tool for studying the behaviour, health and welfare of animals in recent years. A surveillance system using microphone arrays of Kinects was developed for automatically monitoring birds’ abnormal vocalisations during the night. Based on the principle of time-difference of arrival (TDOA) of sound source localisation (SSL) method, Kinect sensor direction estimations were very accurate. The system had an accuracy of 74.7% in laboratory tests and 73.6% in small poultry group tests for different area sound recognition. Additionally, flocks produced an average of 40 sounds per bird during feeding time in small group tests. It was found that, on average, each normal chicken produced more than 53 sounds during the daytime (noon to 6:00 p.m.) and less than one sound at night (11:00 p.m.–3:00 a.m.). This system can be used to detect anomalous poultry status at night by monitoring the number of vocalisations and area distributions, which provides a practical and feasible method for the study of animal behaviour and welfare.

show abstract

…”

Section: Methodsmentioning

confidence: 99%

A Sound Source Localisation Analytical Method for Monitoring the Abnormal Night Vocalisations of Poultry

Lao

Teng

2018

Sensors

View full text Add to dashboard Cite

show abstract

“…A pressing problem is the effect of background noise, reflections and interference. A number of algorithms have been developed to solve this issue, among which we can distinguish two basic methods: using estimators of Time Differences of Arrival (TDOA) and estimators of spatial spectrum distribution [1][2][3]. To a large degree, the efficiency of DOA estimation depends on the fulfilment of the conditions of linearity and isotropic character of the transmission medium and the assumption that the signal source is located at a large distance, so the wave reaching the microphone array can be treated as a plane wave [4].…”

Section: Introductionmentioning

confidence: 99%

Measurements of Vehicle Azimuth Using Acoustic Signals

MADEJ

2023

Quality Production Improvement and System Safety

View full text Add to dashboard Cite

Abstract. The location of objects based on the analysis of acoustic signals is widely used in various civil and military systems. Applications that allow the users to determine the location of the sound source are used, for example, in conference rooms for automatic speaker location, enabling unattended camera control, detecting and tracking the movement of objects in area surveillance systems, etc. The paper presents a system for determining the azimuth of a moving motor vehicle developed at the Military Institute of Engineer Technology in cooperation with the Wroclaw University of Technology. The system is designed for the detection, identification and location of armored vehicles and trucks. The use of acoustic signal analysis methods to locate objects allowed for the construction of passive systems that are difficult to detect. This property is particularly important in area surveillance systems and military equipment designs.

show abstract

“…Therefore, in-air acoustic sensing with sonar microphone arrays has become an active research topic in the last decade [3][4][5][6][7]. This sensing modality can perform well in indoor industrial environments with rough conditions, generate spatial information from that environment, and be used for autonomous activities such as navigation or simultaneous localisation and mapping (SLAM).…”

Section: Introductionmentioning

confidence: 99%

Real-Time Sonar Fusion for Layered Navigation Controller

Jansen

Laurijssen

Steckel

2022

Sensors

View full text Add to dashboard Cite

Navigation in varied and dynamic indoor environments remains a complex task for autonomous mobile platforms. Especially when conditions worsen, typical sensor modalities may fail to operate optimally and subsequently provide inapt input for safe navigation control. In this study, we present an approach for the navigation of a dynamic indoor environment with a mobile platform with a single or several sonar sensors using a layered control system. These sensors can operate in conditions such as rain, fog, dust, or dirt. The different control layers, such as collision avoidance and corridor following behavior, are activated based on acoustic flow queues in the fusion of the sonar images. The novelty of this work is allowing these sensors to be freely positioned on the mobile platform and providing the framework for designing the optimal navigational outcome based on a zoning system around the mobile platform. Presented in this paper is the acoustic flow model used, as well as the design of the layered controller. Next to validation in simulation, an implementation is presented and validated in a real office environment using a real mobile platform with one, two, or three sonar sensors in real time with 2D navigation. Multiple sensor layouts were validated in both the simulation and real experiments to demonstrate that the modular approach for the controller and sensor fusion works optimally. The results of this work show stable and safe navigation of indoor environments with dynamic objects.

show abstract

Direction of Arrival Estimation and Localization Using Acoustic Sensor Arrays

Cited by 17 publications

References 13 publications

A Sound Source Localisation Analytical Method for Monitoring the Abnormal Night Vocalisations of Poultry

A Sound Source Localisation Analytical Method for Monitoring the Abnormal Night Vocalisations of Poultry

Measurements of Vehicle Azimuth Using Acoustic Signals

Real-Time Sonar Fusion for Layered Navigation Controller

Contact Info

Product

Resources

About