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Processor dependent bias of spatial spectral estimates from coprime sensor arrays
Radienxe Bautista1, John R Buck2
1Sensors and Sonar Department, Naval Undersea Warfare Center, 1176 Howell Street, Newport, Rhode Island 02841, USA.
The Journal of the Acoustical Society of America
|July 2, 2018
Summary
Coprime sensor arrays (CSAs) offer efficient direction-of-arrival estimation. The product-processed CSA provides an unbiased spatial power spectral density estimate at large apertures, unlike conventional beamforming methods.
Area of Science:
- Signal Processing
- Array Signal Processing
- Sensor Networks
Background:
- Coprime sensor arrays (CSAs) enable direction-of-arrival (DOA) estimation of numerous sources with fewer sensors.
- Finite aperture array processing smears the spatial power spectral density (PSD) via a kernel function dependent on array geometry and signal processing.
- Understanding the asymptotic behavior of these kernel functions is crucial for accurate source localization.
Purpose of the Study:
- To analyze the asymptotic behavior of kernel functions for two different processors applied to a CSA geometry in the large aperture limit.
- To compare the performance of product-processed CSAs and conventionally beamformed CSAs (CBF CSAs) against a uniform line array (ULA) baseline.
- To investigate the impact of spatially correlated Gaussian noise on PSD estimates from CSA processors.
Main Methods:
- Asymptotic analysis of kernel functions for large aperture sensor arrays.
- Comparison of kernel functions for product-processed CSAs, CBF CSAs, and a uniform line array (ULA).
- Simulation of spatially correlated Gaussian noise to evaluate PSD estimation biases.
Main Results:
- The product-processed CSA's spatial power spectral density (PSD) estimate is asymptotically unbiased at large apertures, similar to a ULA.
- The conventionally beamformed CSA (CBF CSA) estimate exhibits asymptotic bias at large apertures.
- Bias issues in PSD estimates are highlighted when using CSA processors with spatially correlated Gaussian noise.
Conclusions:
- Product-processed CSAs are asymptotically unbiased for DOA estimation in the large aperture regime.
- Conventional beamforming on CSAs introduces bias, limiting their accuracy for high-resolution source localization.
- The choice of CSA processor significantly impacts the reliability of PSD estimation, especially in the presence of noise.
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