Sensor Array Phase Enhancement for Directionality
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Solution Overview
Problem
Conventional beamforming systems face challenges in improving directionality without increasing the number of sensor elements, associated hardware, and computational costs, while maintaining low noise immunity and uniform frequency response.
Innovation Solution
The approach involves widening the nulls of the beam pattern by applying a phase enhancement process that adjusts the electrical phase difference between sensor signals, using a phase expansion function to move off-axis noise signals into the null regions, thereby improving directionality without adding sensor elements or increasing computational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of sensor elements is increased to improve directionality, then directionality is improved, but device complexity and hardware costs increase
Solution Approach 1:
The patent changes the electrical phase parameter of sensor signals through a phase enhancement process. By adjusting phase differences between sensor elements and applying phase expansion functions, the system achieves improved directionality and widened nulls without adding physical sensor elements, thereby resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent transitions from spatial dimension (adding more sensor elements) to phase dimension (manipulating electrical phase differences). This dimensional shift allows achieving better directionality through phase space manipulation rather than physical space expansion, reducing hardware complexity while maintaining or improving performance
2Measurement precision
If the number of sensor elements is increased to improve directionality, then directionality is improved, but manufacturing costs increase
Solution Approach 1:
The invention modifies electrical phase parameters through signal processing rather than changing physical hardware configuration. This approach avoids the costs associated with manufacturing and calibrating additional sensor elements, achieving improved directionality through low-cost phase enhancement processing
Solution Approach 2:
The patent replaces mechanical/physical expansion (adding sensor elements) with electronic/software-based phase manipulation. This substitution eliminates the need for additional hardware manufacturing, reducing manufacturing costs while achieving the same or better directionality improvement
3Measurement precision
If conventional beamforming is used to improve directionality, then directionality is improved, but side lobes and noise immunity increase
Solution Approach 1:
The patent converts the harmful side lobes into beneficial widened nulls through phase enhancement. By manipulating phase differences, the system transforms regions of high sensitivity (side lobes) into regions of low sensitivity (widened nulls), thereby reducing noise immunity and improving directionality simultaneously
Solution Approach 2:
Instead of concentrating energy into narrow beams (conventional approach), the patent inverts the approach by creating widened nulls through phase expansion functions. This inversion strategy achieves directionality improvement by suppressing unwanted directions more effectively rather than by enhancing desired directions
4Measurement precision
If conventional beamforming is used to improve directionality, then directionality is improved, but frequency response uniformity deteriorates
Solution Approach 1:
The patent applies frequency-dependent phase enhancement parameters to maintain uniform frequency response. By adjusting phase expansion functions across different frequency bins, the system achieves improved directionality while compensating for frequency-dependent variations, thereby maintaining response uniformity across the frequency spectrum
Data Source
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AI summary
A method for signal sensitivity matching, the method comprising: generating a first input signal from a first sensor (A) in a sensor array and a second input signal from a second sensor (B) in the sensor array, wherein the first input signal and the second input signal are respectively representable, at least at one frequency, by a first input vector and a second input vector, each of the first input vector and the second input vector having a phase component and a magnitude component; processing the first input signal and the second input signal, the processing including using the magnitude component of the first input vector and the second input vector to obtain respectively a first output vector corresponding to the first input vector and a second output vector corresponding to the second input vector, each of the first output vector and the second output vector having a magnitude that is substantially equal to a mathematical mean of the magnitudes of two or more input vectors, the two or more input vectors including the first input vector, the second input vector, and zero or more other input vectors generated from zero or more other input signals generated from zero or more other input signal sensors in the sensor array; and generating an output signal having a magnitude that is a function of at least one of the first output vector and the second output vector.