Conformal Cylindrical Array Sound Source Localization at the Presence of Shadowed Elements

Sound source localization provides an absorbing capability for unmanned aerial vehicles (UAVs) in scenarios, such as search and rescue operations. The shape fusion between the sound array and UAVs forms a special conformal property that is drawing more and more attention. However, the inevitable shadow effect caused by shape fusion seriously degrades the degrees of freedom (DOF) of the array. In this article, a signal reconstruction-based direction of arrival (DOA) estimation method is proposed to address this limitation. First, we establish a restricted signal model for the conformal cylindrical array (CCA), and then based on frequency domain energy detection, the elements are divided into receiving restricted elements and receiving normal elements. Second, according to the position vector of receiving restricted elements, the approximate range of the DOA is roughly estimated to reduce the complexity. Meanwhile, the signals of receiving restricted elements are reconstructed on the basis of receiving normal elements to eliminate the shadow effect and increase the DOF. Finally, in the estimated approximate range of the DOA, the precise DOA is estimated by peak search. We also derive the 2-D Cramer-Rao lower bound (CRLB) for the CCA. Simulations show that the proposed SR-MUSIC-RS method can achieve satisfactory performance with lower complexity, and the root mean squared error is close to that of general signal model with normal elements.

Automated summary

This article proposes a signal reconstruction-based method for direction of arrival (DOA) estimation to address the shadow effect caused by shape fusion in sound source localization. By dividing the array into restricted elements and normal elements, and reconstructing the signal of restricted elements, the degrees of freedom are increased and the accuracy of DOA estimation is improved.