Abstract

Beamformers have been widely used to enhance signals from a desired direction and suppress noise and interfering signals from other directions. Constant beamwidth beamformers enable a fixed beamwidth over a wide range of frequencies. Most of the existing approaches to design constant beamwidth beamformers are based on optimization algorithms with high computational complexity and are often sensitive to microphone mismatches. Other existing methods are based on adjusting the number of sensors according to the frequency, which simplify the design, but cannot control the sidelobe level. Here, we propose a window-based technique to attain the beamwidth constancy, in which different shapes of standard window functions are applied for different frequency bins as the real weighting coefficients of microphones. Thereby, not only do we keep the beamwidth constant, but we also control the sidelobe level. Simulation results show the advantages of our method compared with existing methods, including lower sidelobe level, higher directivity factor, and higher white noise gain.

Highlights

  • Beamformers, or spatial filters, enhance signals from a desired direction and suppress noise and interfering signals from other directions

  • Many existing methods have been investigated to obtain constant beamwidths [6,7,8,9,10,11,12]. These methods are mainly based on optimization algorithms with high computational design complexity, and they are often sensitive to microphone mismatches

  • All of the simulated uniform linear arrays are configured with M = 11 omnidirectional microphones, with an interelement spacing equal to δ = 3.5

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Summary

Introduction

Beamformers, or spatial filters, enhance signals from a desired direction and suppress noise and interfering signals from other directions. The basic approach of solving this problem is to design a constant beamwidth beamformer, where the beampattern maintains a fixed beamwidth over a wide frequency band. The main idea behind this approach is to change the effective array aperture in each frequency bin to maintain the beamwidth constant over the desired frequency band. This method is characterized by low computational complexity, but cannot control the sidelobe level. The main idea is to apply different shapes of windows for different frequency bins as real weighting coefficients of microphones, so that the beamwidth is maintained constant by controlling the window parameters.

Signal Model
Beamformer
Beamwidth
Window-Based Acoustic Beamformer with a Constant Beamwidth
Modified Rectangular Window
Lowest and Highest Frequencies
The Parameter g
DPSS Window
The Parameter u0
Kaiser Window
The Parameter β
The Parameter r
Experiments and Results
Optimal Window Parameter
Performance Measures
Wideband Beampatterns with a Constant Beamwidth Using Different Windows
Chebyshev Window
Directivity Factor and White Noise Gain as Function of Frequency
Beamwidth as Function of Frequency
Conclusions

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