Augmented Lagrangian algorithm based on fixed point iteration for sound source identification
HE Yansong1,2, JIA Chenyang1, HUANG Linsen1, ZAN Ming1, XU Zhongming1,2
1. School of Automotive Engineering, Chongqing University, Chongqing 400030,China;
2. The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400030,China
Abstract:Near-field acoustic holography based on the equivalent source method is an important method for sound source identification. The conventional Tikhonov regularization method is limited to relatively low frequencies, and the effect of the sound field reconstruction of high-frequency sound sources is poor. While the wideband acoustic holography (WBH)method based on the steepest descent method has better effects at middle-to-high frequencies. In order to widen the frequency range of sound field reconstruction and to improve the resolution of sound source identification, this paper proposes an equivalent source method based on augmented Lagrangian method(ALM) for sound source identification, which transforms the L1-norm regularized model into the minimization problem of augmented Lagrangian equation, and fixed-point iteration is applied to gain the source strength. Simulations and experiments results show that, compared with the three methods of Tikhonov regularization, wideband acoustic holography and fast iterative shrinking threshold algorithm(FISTA), the proposed method is suitable for a wider frequency range and has good adaptability to different holographic distances and signal-to-noise ratios.
Key words: equivalent source method; sound source identification; compressive sensing; augmented Lagrangian method(ALM)
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