Tracking moving wideband sound sources is one of the most challenging issues in the acoustic array signal processing which is based on the direction of arrival(DOA) estimation. Compressive sensing(CS) is a recent theo...Tracking moving wideband sound sources is one of the most challenging issues in the acoustic array signal processing which is based on the direction of arrival(DOA) estimation. Compressive sensing(CS) is a recent theory exploring the signal sparsity representation, which has been proved to be superior for the DOA estimation. However, the spatial aliasing and the offset at endfire are the main obstacles for CS applied in the wideband DOA estimation. We propose a particle filter based compressive sensing method for tracking moving wideband sound sources. First, the initial DOA estimates are obtained by wideband CS algorithms. Then, the real sources are approximated by a set of particles with different weights assigned. The kernel density estimator is used as the likelihood function of particle filter. We present the results for both uniform and random linear array. Simulation results show that the spatial aliasing is disappeared and the offset at endfire is reduced. We show that the proposed method can achieve satisfactory tracking performance regardless of using uniform or random linear array.展开更多
The main factors deciding the compressive strength of binder backfill body are tailing density and binder dosage in binder backfill materials. Based on the antecedent of certain pulp density, the method of increasing ...The main factors deciding the compressive strength of binder backfill body are tailing density and binder dosage in binder backfill materials. Based on the antecedent of certain pulp density, the method of increasing the tailing density and reducing the binder dosage, or the manner of cutting down the tailing density and gaining the binder dosage are taken to guarantee the strength of backfill body. The problem that should be solved is how to determine the tailing density and the binder dosage rationally. This paper tries to realize the correct selection of the tailing density and the binder dosage in computer with the method of fuzzy mathematics.展开更多
基金supported by the NFSC Grants 51375385 and 51675425Natural Science Basic Research Plan in Shaanxi Province of China Grants 2016JZ013
文摘Tracking moving wideband sound sources is one of the most challenging issues in the acoustic array signal processing which is based on the direction of arrival(DOA) estimation. Compressive sensing(CS) is a recent theory exploring the signal sparsity representation, which has been proved to be superior for the DOA estimation. However, the spatial aliasing and the offset at endfire are the main obstacles for CS applied in the wideband DOA estimation. We propose a particle filter based compressive sensing method for tracking moving wideband sound sources. First, the initial DOA estimates are obtained by wideband CS algorithms. Then, the real sources are approximated by a set of particles with different weights assigned. The kernel density estimator is used as the likelihood function of particle filter. We present the results for both uniform and random linear array. Simulation results show that the spatial aliasing is disappeared and the offset at endfire is reduced. We show that the proposed method can achieve satisfactory tracking performance regardless of using uniform or random linear array.
文摘The main factors deciding the compressive strength of binder backfill body are tailing density and binder dosage in binder backfill materials. Based on the antecedent of certain pulp density, the method of increasing the tailing density and reducing the binder dosage, or the manner of cutting down the tailing density and gaining the binder dosage are taken to guarantee the strength of backfill body. The problem that should be solved is how to determine the tailing density and the binder dosage rationally. This paper tries to realize the correct selection of the tailing density and the binder dosage in computer with the method of fuzzy mathematics.
