Real-Time FIR Filter Coefficient Generation for Low-Memory Hardware
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Solution Overview
Problem
In ultrasound imaging systems, high-order filters require significant storage capacity for pre-stored filter coefficients, which is inefficient, and adaptive methods are complex and resource-intensive, making them unsuitable for programmable devices with limited resources.
Innovation Solution
Generating filter coefficients in real time based on the varying cut-off angular frequency, using a method that looks up intermediate values in memory tables and multiplies them to calculate coefficients, reducing storage needs and hardware resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If filter coefficients are pre-stored in memory for high-order filters, then filtering accuracy is maintained, but storage capacity requirements become prohibitively high
Solution Approach 1:
The patent extracts only the essential parameters (cut-off angular frequency values) from the complete filter coefficient sets, storing only these extracted parameters in memory rather than storing all coefficient data. This reduction from storing complete coefficient sets to storing only frequency parameters dramatically reduces storage requirements while maintaining filtering accuracy through real-time coefficient generation.
Solution Approach 2:
The patent pre-calculates and stores a lookup table of filter coefficients corresponding to different cut-off angular frequencies before operation. During runtime, the system only needs to store and lookup these pre-computed coefficient sets or frequency parameters, rather than storing all possible filter coefficients for every possible frequency, significantly reducing memory requirements.
2Adaptability or versatility
If adaptive filter coefficient generation is implemented, then filter adaptability to varying frequencies is improved, but algorithm complexity and resource consumption increase
Solution Approach 1:
The patent pre-computes filter coefficients for a range of cut-off angular frequencies and stores them in a lookup table before the device operates. When adaptation is needed, the system simply retrieves pre-computed coefficients corresponding to the current frequency rather than performing complex real-time calculations, thus achieving adaptability with minimal computational resources.
Solution Approach 2:
The system uses the cut-off angular frequency parameter itself to directly index into the pre-computed lookup table and retrieve the appropriate filter coefficients. The frequency parameter serves both as the control signal and as the key for automatic coefficient selection, eliminating the need for complex adaptive algorithms while maintaining frequency adaptability.
3Reliability
If complete filter coefficient sets are stored for time-varying filters, then filtering performance is maintained, but hardware resource consumption becomes excessive
Solution Approach 1:
The patent identifies and extracts only the critical frequency parameter (cut-off angular frequency) that determines filter behavior, storing only this extracted parameter rather than complete coefficient sets. This extraction approach maintains filtering performance by preserving the essential frequency information while dramatically reducing the data storage and processing resources required.
Solution Approach 2:
Instead of storing and processing complete filter coefficient sets, the system uses a simplified representation (cut-off angular frequency values or reduced coefficient tables) that can be easily copied and referenced. This copying approach allows the system to maintain filtering performance using lightweight data structures that consume minimal hardware resources.
Data Source
AI summary
The present invention provides a method and device for generating a filter coefficient in real time. The method includes: looking up a converted window function value in a converted window function table based on a current coefficient index; generating a current cut-off angular frequency; generating a look-up table address based on the current coefficient index, the filter order and the current cut-off angular frequency and looking up a sine value in a sine table based on the look-up table address; and multiplying the converted window function value by the sine value to obtain the filter coefficient. The device includes a first memory, a second memory, a look-up table address generation module and a first multiplier. The present invention is easily implemented with low hardware resource consumption and high flexibility, and is particularly applicable for the hardware implementation of high-order finite impulse response filters.