Abstract
Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.
Highlights
Intelligent transportation and unmanned systems have made new demands to the parameter estimation of sequential movement events of vehicles, such as noise insensitive, scalable, and portable implementation, etc
The results show that the proposed method has better robustness to the uncorrelated wind noise than the narrow-band multiple signal classification (MUSIC) method, sub-band method [20] and classical wideband two-sided correlation transformation (TCT) method [31]
Since the narrowband MUSIC method [19] chooses the fixed frequency within the bandwidth to calculate manifold matrix, the DOA estimation results will deviate significantly when the area near the fixed frequency is heavily contaminated by wind noise, which can be proved by the few large deviation in the Temporal interval 1 and Temporal interval 2 in Figure 13a.The sub-band method [20] selects the sub-band that has the largest sub-band magnitude squared coherence (SMSC) for DOA estimation
Summary
Intelligent transportation and unmanned systems have made new demands to the parameter estimation of sequential movement events of vehicles, such as noise insensitive, scalable, and portable implementation, etc. We will propose a wind noise robust DOA estimation method based on a small aperture microphone array system. Independent from apertures, the MSC of the wind noise (0~4 kHz) is close to zero, while the MSC of the corresponding target acoustic signal is close to 1 [26] Due to this difference, the spatial coherence is used to select the frequency, which is less affected by the wind noise and to estimate the DOA of a moving vehicle in [19]. We propose a multiple high SMSC sub-bands weighting strategy and integrate it into the moving vehicle DOA estimation method of our previous work [20].
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