Phased Array Wavefront Segmentation for Data Loss Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Phased array transducers generate data at a peak rate exceeding the capabilities of standard interfaces, leading to data loss and inefficiencies in processing and transmission, particularly as the number of transducers and sampling rate increase.
Innovation Solution
The method involves fractionalizing the depth of signal penetration into quantum blocks (Q-blocks) and processing data in fractions of time, allowing for efficient data transmission through standard interfaces by buffering and assembling digital signals from multiple time fractions into image frames, optimizing memory usage and maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of transducers and sampling rate are increased to improve imaging quality and coverage, then the data generation rate increases, but the standard interface cannot handle the data transmission rate leading to data loss
Solution Approach 1:
The patent divides the continuous data stream from the phased array into discrete time-fractionated packets. Each packet contains data from a specific time window corresponding to a particular depth range. This segmentation allows the high-rate data to be processed in manageable chunks that can be transmitted through standard interfaces without loss, while maintaining the complete imaging information across all time fractions.
Solution Approach 2:
The system performs preliminary data processing and sorting in the front-end circuitry before transmission. Data from multiple transducers are pre-organized into time-fractionated packets with proper timing information embedded. This preliminary action reduces the processing burden on the central processing unit and ensures data is ready for immediate transmission through standard interfaces at the required high rate.
2Productivity
If the data transmission rate is increased to match the data generation rate from the array, then real-time imaging is achieved, but standard interfaces cannot handle the required data rate
Solution Approach 1:
The patent segments the high-volume data stream into smaller time-fractionated packets that can be transmitted through standard interfaces. By dividing the data into manageable chunks corresponding to different time fractions and depth ranges, the system maintains real-time imaging capability while using conventional interface hardware, avoiding the need for complex high-speed specialized interfaces.
Solution Approach 2:
The system employs periodic transmission of time-fractionated data packets through the standard interface. Data from different time fractions are transmitted in a systematic periodic sequence, allowing the central processing unit to reconstruct real-time images from these periodic data streams. This periodic action synchronizes data transmission with the imaging requirements while utilizing standard interface capabilities.
3Measurement precision
If all returning wave fronts are processed simultaneously to maintain image quality, then memory requirements increase significantly, but memory constraints limit the ability to process all data
Solution Approach 1:
The patent segments the processing of returning wave fronts into distinct time-fractionated groups. Instead of processing all wave fronts simultaneously, the system processes them in sequential time fractions, each corresponding to a specific depth range. This segmentation dramatically reduces the memory required at any given moment while ensuring all data contributes to the final image quality through systematic reconstruction.
Solution Approach 2:
The system performs preliminary organization of returning wave fronts into time-fractionated packets at the front end, before data transmission. This preliminary sorting into depth-specific groups allows efficient memory utilization during processing, as only the relevant time fraction data needs to be held in memory at any moment, yet all data is eventually processed to maintain complete image quality.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the retention of image quality within memory constraints, reducing data loss and optimizing memory requirements, allowing for real-time creation of image frames despite the high data rates produced by phased arrays.
Implementation Method 1
generating a first pulse from a plurality of transducers in a phased array; receiving a first returning wave front from an intersection of the first pulse with a change in acoustic impedance
Implementation Method 2
capturing a first plurality of samples from a transducer response by converting the first plurality of samples from the first returning wave front to a plurality of first digital signals
Data Source
AI summary
Methods and systems for storing and processing a plurality of fractions of imaging data thereby minimizing the amount of cache memory necessary while controlling data loss and the resulting image quality.