Summary

This paper presents a practical wavelet-based denoising technique for time-domain reflectometry (TDR) waveforms to substantially increase TDR dynamic range and improve s-parameter measurement accuracy. Readers will learn how multiresolution thresholding and careful choice of wavelet parameters reduce noise while preserving reflection timing and amplitude for improved measurement fidelity.

Key Takeaways

• Apply multiscale wavelet thresholding to TDR waveforms to suppress broadband and low-level noise without smearing reflection edges.
• Choose an appropriate mother wavelet and decomposition depth based on TDR pulse bandwidth and the waveform’s time-resolution requirements.
• Set and tune level-dependent thresholds (e.g., VisuShrink, SURE) and decide between hard/soft thresholding using noise estimates from pre-pulse regions.
• Integrate denoised time-domain data to extend measurable dynamic range and improve s-parameter extraction accuracy in TDR-based systems.
• Validate denoising performance with SNR and dynamic-range metrics and be mindful of edge effects and computational trade-offs for real-time use.

Who Should Read This

Signal-processing and measurement engineers (intermediate–advanced) working on TDR, radar/cable diagnostics, or s-parameter extraction who want to increase dynamic range of time-domain measurements.

Still RelevantAdvanced

Topics