Signal Resampling With MASH Timing Control for Smooth Rate Changes
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Solution Overview
Problem
Existing signal processing techniques for converting sample rates are inefficient due to high computational and storage requirements, complex hardware implementations, and inability to smoothly change sampling rates over time, especially when dealing with non-integer multiple sample rate conversions.
Innovation Solution
A system utilizing a shaping filter with a dual-modulus counter and Multi-stAge noise Shaping Digital Delta-Sigma Modulator (MASH DDSM) for real-time or offline signal processing, allowing for smooth sampling rate changes and efficient resampling without excessive resource usage, employing a windowed-sinc filter and error feedback modulators to manage interpolation and timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional rational resampling with digital lowpass filter is used, then sample rate conversion can be performed, but computational complexity and processing time increase significantly
Solution Approach 1:
The resampling process is divided into two separate stages: first interpolating the signal by factor L, then decimating by factor M. This segmentation allows each stage to be optimized independently, reducing overall computational complexity compared to performing the full rational resampling L/M in one complex filtering operation.
Solution Approach 2:
The digital lowpass filter operation is extracted and performed separately between the interpolation and decimation stages. By taking out the filtering operation and positioning it optimally in the signal chain, the method reduces the number of filter coefficients that need to be computed and stored, thereby reducing processing time while maintaining conversion accuracy.
2Measurement precision
If large interpolation ratio L/M is used for rational resampling, then more precise sample rate conversion is achieved, but coefficient storage and processing requirements increase
Solution Approach 1:
The large interpolation ratio L/M is segmented into two smaller integer factors L and M. Instead of designing and storing coefficients for a single large-ratio filter, the system uses separate filters for interpolation (ratio L) and decimation (ratio M). This segmentation dramatically reduces the number of coefficients that need to be stored, as each filter has fewer coefficients than the equivalent single-stage filter would require.
Solution Approach 2:
The system dynamically adjusts the interpolation and decimation factors L and M based on the desired sample rate conversion ratio. This dynamic approach allows the use of smaller, more manageable filter coefficients while achieving the same overall resampling effect, reducing storage requirements while maintaining precision.
3Adaptability or versatility
If programmable L/M ratio is implemented for flexibility, then adaptability to different sample rates is improved, but hardware implementation complexity increases
Solution Approach 1:
The programmable resampling ratio is segmented into two independent programmable parameters L and M. This segmentation simplifies hardware implementation because each parameter can be controlled separately through simple integer division operations, avoiding the need for complex programmable filter structures that would be required for direct implementation of arbitrary L/M ratios.
Solution Approach 2:
The system replaces complex programmable hardware filtering structures with simpler digital signal processing operations: integer-based interpolation by factor L followed by decimation by factor M. This substitution of mechanical/complex hardware with digital algorithms reduces hardware complexity while maintaining full programmability of the sample rate conversion ratio.
4Productivity
If fixed sample rate conversion is used, then processing efficiency is maintained, but ability to change sampling rates smoothly over time is lost
Solution Approach 1:
The system transitions from fixed sample rate conversion to dynamic sample rate conversion by making the interpolation factor L and decimation factor M time-varying parameters. This allows the effective sample rate conversion ratio to change smoothly over time in a programmable manner, enabling applications such as variable pitch playback, time-stretching, and adaptive sampling rate matching while maintaining processing efficiency through the use of simple integer-based operations.
Data Source
AI summary
An instrument configured to process signal data is disclosed. The instrument is operable to control and or change the sampling rate of the signal data from a first sample rate to a second sample rate different than the first sample rate.