Efficient Sigma-Delta Sensor Array Beamforming.

Area of Science:

• Signal Processing
• Embedded Systems Engineering
• VLSI Design

Background:

• Sensors with sigma-delta modulators (ΣΔMs) are prevalent in various applications, outputting Pulse-Density Modulated (PDM) signals.
• Demodulating PDM signals to Pulse-Code Modulated (PCM) requires high-order decimation filters, increasing costs in sensor arrays.
• Implementing array algorithms like beamforming is resource-intensive due to parallel filter needs.

Purpose of the Study:

• To propose a novel, cost-effective architecture for beamforming algorithm implementation.
• To fuse delay and decimation operations using Maximally Flat (MAXFLAT) filters.
• To reduce computational and storage resource requirements for sensor array processing.

Main Methods:

• Developed a novel architecture integrating delay and decimation operations.
• Utilized Maximally Flat (MAXFLAT) filters for enhanced performance.
• Implemented a delay-and-sum (DAS) beamformer as a proof of concept.

Main Results:

• The proposed architecture requires 52% less storage resources compared to state-of-the-art methods.
• Achieved a 19% reduction in computational resources.
• Demonstrated feasibility for beamforming with specific spatial and frequency requirements.

Conclusions:

• The novel architecture makes sensor array processing, particularly beamforming, more affordable.
• This approach offers significant resource savings for embedded systems and VLSI circuits.
• The fusion of delay and decimation presents an efficient solution for PDM signal processing.