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Geometry calibration is an inherent challenge in distributed acoustic sensor networks. To mitigate this problem, a passive geometry calibration approach based on distributed damped Newton optimization is proposed. Specifically, a geometric cost function incorporating direction of arrivals (DoAs) and time difference of arrivals (TDoAs) is first formulated, and then its identifiability conditions are given. Next, to achieve a distributed geometry calibration, the cost function is split into multiple local cost functions that are assigned to every node. After that, a distributed damped Newton optimization is presented to retrieve the geometry of microphone nodes and synchronize the internal delay between each two neighboring nodes. Finally, computational complexity and transmission bandwidth requirements are further analyzed. Compared with the existing approaches, the proposed method estimates the geometry structure of microphone networks in a distributed manner. Moreover, it requires a small number of acoustic sources. Experimental results show the validity of the proposed method.
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