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In this paper, we propose an energy-efficient compressed data aggregation framework for three-dimensional underwater acoustic sensor networks (UASNs). The proposed framework consists of two layers, where the goal is to minimize the total energy consumption of transmitting the data sensed by nodes. The lower layer is the compressed sampling layer, where nodes are divided into clusters. Nodes are randomly selected to conduct sampling, and then send the data to the cluster heads through random access channels. The upper layer is the data aggregation layer, where full sampling is adopted. We also develop methods to determine the number of clusters and the probability that a node participates in data sampling. Simulation results show that the proposed framework can effectively reduce the amount of sampling nodes, so as to reduce the total energy consumption of the UASNs.

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.