Signal Processor Phase Deviation Estimation
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Solution Overview
Problem
Existing signal processing technologies face challenges in accurately and efficiently computing affine transformations between suspect and reference signals, particularly in digital computing environments, due to errors introduced by discrete digital logic and memory constraints, which complicates signal detection and recognition applications.
Innovation Solution
A method and circuit for estimating the offset between reference and suspect signals using phase deviation metrics, involving phase estimation and direct least squares techniques to determine linear transforms and phase shifts, allowing for efficient alignment of signals despite transformations such as rotation, scaling, and translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If discrete digital logic is used to compute affine transformations, then computational efficiency is improved, but measurement precision deteriorates due to quantization errors
Solution Approach 1:
The patent pre-computes and stores transformation parameters (rotation angles, scale factors, shear values) in lookup tables before actual signal processing occurs. This preliminary action allows the system to retrieve pre-calculated values during runtime, avoiding complex real-time calculations that would require high precision while maintaining computational efficiency.
Solution Approach 2:
The patent employs fixed-point arithmetic instead of floating-point arithmetic for transformation calculations. This approach uses simpler, faster digital logic circuits that are easier to implement in hardware, accepting some loss in precision in exchange for significant gains in computational speed and hardware simplicity.
2Manufacturing precision
If memory bandwidth is increased to store transformation parameters, then manufacturing precision is improved, but device complexity worsens
Solution Approach 1:
The patent divides transformation parameters into multiple segments or components (e.g., separating integer and fractional parts of transformation values, or dividing rotation and scaling parameters into independent blocks). This segmentation allows each parameter block to be stored in separate, smaller memory units, reducing the complexity of any single memory system while maintaining overall precision through coordinated use of multiple segments.
3Reliability
If signal transformations are computed with high precision, then reliability is improved, but productivity deteriorates due to increased computational cost
Solution Approach 1:
The patent applies transformation precision selectively based on the specific application requirements and signal characteristics. For critical detection tasks, higher precision is used, while for less critical operations or preliminary processing steps, lower precision suffices. This partial application of high precision maintains reliability where needed while improving overall processing throughput by not unnecessarily applying high precision throughout the entire processing pipeline.
Data Source
AI summary
A phase deviation method determines an offset between a reference and suspect signal by analyzing a phase deviation surface created by computing a deviation metric for phase shift and then analyzing a surface formed from the deviation metrics for an array of offsets. The phase deviation method analyzes the deviation surface to determine an offset that minimizes phase deviation. This method is applied at increasing levels of detail to refine the determination of the offset.