Spectral Averaging for RF Noise Floor Reduction
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Solution Overview
Problem
Conventional spectral analyzers face limitations in dynamic range due to electrical noise and distortion, particularly in RF spectral analysis, leading to inefficient separation of signals from random noise, resulting in biased tone display and significant power loss.
Innovation Solution
The technique involves cross-power spectrum analysis of time-domain samples, accumulating and averaging cross-power spectra from multiple acquisitions to reduce noise levels and improve dynamic range, allowing for better signal separation and preservation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If signal attenuation is increased to reduce distortion, then distortion is reduced, but noise performance deteriorates
Solution Approach 1:
The signal processing is divided into multiple independent acquisitions or sweeps, where each acquisition processes the signal separately. By segmenting the measurement into multiple parts and combining the results, the system achieves both low distortion (through attenuation in each sweep) and low noise (through averaging of multiple sweeps), resolving the contradiction between distortion reduction and noise performance.
2Measurement precision
If conventional spectral analysis is used, then spectral measurement is obtained, but signal separation from noise is inefficient
Solution Approach 1:
The system performs continuous spectral measurements over multiple acquisitions, continuously accumulating useful signal information while random noise averages out. This continuous measurement approach maintains high measurement precision while improving signal separation from noise through the accumulation of multiple measurements.
Solution Approach 2:
The signal is measured multiple times (creating copies of the measurement), and these copies are combined through averaging. The useful signal information is preserved across copies while random noise varies between copies, allowing separation of signal from noise through the copying and averaging process.
3Object-affected harmful factors
If multiple acquisitions are averaged, then noise floor is reduced, but measurement time increases
Solution Approach 1:
The system performs a sufficient number of acquisitions to achieve the desired noise floor reduction, rather than attempting to minimize measurement time. By accepting the time required for multiple acquisitions, the system achieves arbitrarily low noise floors through averaging, prioritizing noise reduction over measurement speed.
Data Source
AI summary
Performing spectral analysis may include, for each of multiple acquisitions: a receiving a plurality of time-domain samples, cross-power spectrum analyzing first and second portions of the plurality of samples resulting in cross-power spectra, and accumulating a vector sum of the cross-power spectra including any cross-power spectra from previous acquisitions. Performing spectral analysis may also include calculating a vector average based on the accumulated vector sum and quantity of acquisitions. Performing spectral analysis may also include displaying the magnitude of the vector average.