Design of the Independent Rescue System Based on the Passive Sound Source Localization and Machine Vision

2015 ◽  
Vol 713-715 ◽  
pp. 966-969
Author(s):  
Sheng Dong ◽  
Ai Guo Zhao ◽  
Li Yun Xing ◽  
Fei Wang ◽  
Fang Lei Song ◽  
...  
Keyword(s):  
Machine Vision ◽  
Source Localization ◽  
Sound Source ◽  
Sound Source Localization ◽  
Control Module ◽  
Mobile Client ◽  
Video Information ◽  
Processing Module ◽  
Rescue System ◽  
Communication Control

The purpose of this paper is to design a family or battlefield independent rescue system which is based on passive sound source localization and machine vision, The system consists of five modules: the sound acquisition and processing module based on FPGA, image acquisition and processing module based on TMS320DM6437, video capture and communication control module based on TMS320DM355, motion control module based on MSP430F149, PC server and smart handheld mobile client. It can track target person who need help automatically by recognizing his voice and image, to provide emergency medicines, communication tools, and transmit real-time video information to a server on PC and a mobile client on Andriod platform by wireless network, and be controlled remotely.

scholarly journals Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 532
Author(s):  
Henglin Pu ◽  
Chao Cai ◽  
Menglan Hu ◽  
Tianping Deng ◽  
Rong Zheng ◽  
...  
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Indoor Localization ◽  
Weighting Function ◽  
Signal To Noise Ratio ◽  
Source Separation ◽  
Sound Source Localization ◽  
Angle Of Arrival ◽  
Sound Sources ◽  
Localization Algorithms

Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed by the number of microphones in an array. To this end, this paper proposes a novel multiple blind sound source localization algorithms using Source seParation and BeamForming (SPBF). Our algorithm overcomes the limitations of existing solutions and can locate more blind sources than the number of microphones in an array. Specifically, we propose a novel microphone layout, enabling salient multiple source separation while still preserving their arrival time information. After then, we perform source localization via beamforming using each demixed source. Such a design allows minimizing mutual interference from different sound sources, thereby enabling finer AoA estimation. To further enhance localization performance, we design a new spectral weighting function that can enhance the signal-to-noise-ratio, allowing a relatively narrow beam and thus finer angle of arrival estimation. Simulation experiments under typical indoor situations demonstrate a maximum of only 4∘ even under up to 14 sources.

scholarly journals Multimodal Fusion for Indoor Sound Source Localization

2021 ◽  
pp. 107906
Author(s):  
Jinhui Chen ◽  
Ryoichi Takashima ◽  
Xingchen Guo ◽  
Zhihong Zhang ◽  
Xuexin Xu ◽  
...  
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Multimodal Fusion ◽  
Sound Source Localization
Sign in / Sign up

Export Citation Format

Share Document