Short Description

Conventionally, large sensor arrays are used for source localization to warrant sufficient spatial diversity across sensors to resolve time delays between source observations. It is well known that the precision of delay-based bearing estimation degrades with shrinking dimensions (aperture) of the sensor array. Time-difference of arrival estimation techniques based on cross-correlation of the signals require high oversampling ratios for estimating small time delays. Gradient flow, is a signal conditioning technique for arrays of very small dimensions, which converts time delays between signal observations into relative amplitudes of the time-differentiated signal, by observing gradients (spatial differences). Improved differential sensitivity of gradient sensing allows to shrink the aperture of the sensor array without degrading signal-to-noise ratio. Interestingly, some insects are capable of remarkable auditory localization at dimensions a small fraction of the wavelength, owing to differential processing of sound pressure through inter-tympanal mechanical coupling or inter-aural coupled neural circuits [1].

Your Tasks

• Learn basics on gradient flow localization
• Implement a gradient flow localization algorithm
• Run experiments using an 4mmx4mm MEMS Microphone Array both on simulated and real data
• Documentation

Your Profile

• Motivation and interest in the topic
• Signal Processing
• Matlab

Contact

Martin Hagmüller (hagmueller@tugraz.at or 0316/873 4377)

References

Stanacevic, M.; Cauwenberghs, G., “Micropower gradient flow acoustic localizer,” in IEEE Transactions on Circuits and Systems I: Regular Papers, vol.52, no.10, pp.2148-2157, Oct. 2005 doi: 10.1109/TCSI.2005.853356