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Joint Blind Enhancement and Passive Source Localisation of Acoustic Signals

声信号的联合盲增强和被动源定位

基本信息

批准号：
EP/H012699/1
负责人：
James Hopgood
金额：
$ 12.15万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2009
资助国家：
英国
起止时间：
2009 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FH012699%2F1
关键词：
Joint Blind Enhancement Passive Source

项目摘要

This proposal addresses joint tracking and enhancement of signals received from a target which admits an acoustic signature. Processing of real-world analogue signals measured using a variety of sensors, such as microphones, and which propagate in multipath or reverberant environments such as any building, is fundamental to a variety of applications. Within civilian and domestic settings it is important for teleconferencing and hands-free audio enhancement applications. Within the homeland security and defence sectors it is crucial in a wide variety of fields such as forensics and surveillance, and a number of problems requiring target detection and identification -- for example outdoor gunshot detection and localisation in urban environments.Any signal radiated in a confined space exhibits reverberation, also known as multipath propagation, due to reflections off surrounding obstacles. However, many existing signal processing technologies fail to explicitly model the multipath response. Consequently, multipath causes significant problems in signal enhancement and separation, signal detection, high-resolution source localisation, and joint detection, classification, and localisation technologies -- these are all technologies with which consumers are becoming familiar through every day devices such as mobile telephones and audio playback devices.Blind multipath equalisation can be improved with accurate modelling of the acoustic distortion which, in turn, depends on knowledge of the target-position, thereby requiring target tracking. However, many passive target tracking methods -- those which do not actively emit a signature signal, such as active radar and sonar -- suffer from the presence of multipath leading to substantial errors in tracking. Target tracking can thus be improved by modelling the effect of, or even equalising, the acoustic reverberation from the observations, thereby allowing identification of the true source from signal reflections. Target tracking and blind multipath equalisation should therefore be solved jointly rather than separately.The objective of this 12-month research programme is to address the detrimental effect of multipath mitigation by developing algorithms for joint blind enhancement and passive source localisation of speech sources in an indoor multipath environment.

该方案解决了从允许声学签名的目标接收的信号的联合跟踪和增强。使用各种传感器(如麦克风)测量的、在多径或混响环境(如任何建筑物)中传播的真实世界模拟信号的处理是各种应用的基础。在民用和家庭环境中，这对于电话会议和免提音频增强应用非常重要。在国土安全和国防部门，它在取证和监视等广泛领域以及一些需要目标检测和识别的问题中至关重要--例如户外枪击检测和城市环境中的定位。由于周围障碍物的反射，在受限空间中辐射的任何信号都会产生混响，也称为多径传播。然而，许多现有的信号处理技术无法显式地对多径响应进行建模。因此，多径在信号增强和分离、信号检测、高分辨率信源定位以及联合检测、分类和定位技术方面产生了重大问题--这些都是消费者通过移动电话和音频回放设备等日常设备熟悉的技术。盲多径均衡可以通过对声学失真的准确建模来改进，而声学失真反过来又依赖于目标位置的知识，从而需要目标跟踪。然而，许多被动目标跟踪方法--那些不主动发出特征信号的方法，如有源雷达和声纳--存在多径问题，导致跟踪误差很大。因此，可以通过对来自观测的声学混响的影响进行建模甚至使其均衡来改进目标跟踪，从而允许从信号反射中识别真正的源。因此，目标跟踪和盲多径均衡应该共同解决，而不是分开解决。这个为期12个月的研究计划的目标是通过开发室内多径环境中语音源的联合盲增强和被动源定位算法来解决多径缓解的不利影响。