Millimeter-Wave Spectrum Analysis Using Resonant Half-Mirror Filters
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Solution Overview
Problem
The accuracy of spectrum analysis in the millimeter-wave band above 100 GHz is compromised due to overlapping frequency-converted components and noise, making it difficult to distinguish signal components from noise and spurious components in existing harmonic mixing methods.
Innovation Solution
A millimeter-wave band spectrum analysis device employing a millimeter-wave band filter with planar radio wave half mirrors and resonance frequency change mechanisms, combined with a frequency conversion unit and spectrum detection unit, to selectively extract and convert signal components into a lower frequency band for accurate analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a harmonic mixer is used to measure frequencies above 60 GHz, then the operating frequency range is extended beyond the YTF limit, but frequency-converted components of multiple harmonic orders overlap and increase the noise floor, reducing measurement accuracy
Solution Approach 1:
The patent divides the frequency measurement process into multiple segments by using multiple band-pass filters, each tuned to a specific harmonic order (e.g., 2nd harmonic at 80-160 GHz, 3rd harmonic at 120-240 GHz). This segmentation isolates different harmonic components in the frequency domain, preventing their overlap and allowing accurate measurement of each harmonic order independently.
Solution Approach 2:
The patent extracts specific harmonic components from the mixed signal by using band-pass filters that selectively pass only the desired harmonic order while rejecting others. For example, a band-pass filter tuned to 80-160 GHz extracts the 2nd harmonic component from the mixer output, separating it from the fundamental frequency and other harmonic orders.
2Adaptability or versatility
If multiple harmonic components are mixed in the frequency conversion process, then frequency conversion to intermediate band is achieved, but heterodyne components and image signals overlap with desired signals, making accurate observation difficult
Solution Approach 1:
The patent segments the frequency spectrum into multiple non-overlapping bands using cascaded band-pass filters. Each filter stage is designed to pass a specific frequency range corresponding to a particular harmonic order, thereby separating desired signals from heterodyne components and image signals that would otherwise overlap in the intermediate frequency band.
Solution Approach 2:
The patent introduces band-pass filters as intermediary elements between the mixer and the spectrum analyzer. These filters act as mediators that selectively transmit only the desired harmonic components while blocking unwanted heterodyne and image signals, thereby cleaning the signal before it reaches the detection stage.
3Quantity of substance
If the noise floor increases due to overlapping harmonic components, then all frequency components are captured, but low-level signal components become indistinguishable from noise
Solution Approach 1:
The patent extracts low-level signal components from the noisy mixed signal by using band-pass filters that isolate specific harmonic bands. By extracting only the relevant harmonic components and rejecting others, the filter enhances the signal-to-noise ratio for low-level signals, making them distinguishable from the noise floor.
Solution Approach 2:
The patent applies local quality enhancement by designing band-pass filters with high selectivity in specific frequency regions where low-level signals are expected. Each filter is optimized to provide maximum attenuation of out-of-band noise while maintaining minimal insertion loss for the desired signal band, thereby locally improving the signal-to-noise ratio.
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
The solution provides high selectivity in the frequency domain above 100 GHz, reducing spurious components and enabling accurate spectrum analysis by isolating desired signal components and preventing harmonic distortion, thus improving dynamic range and analysis accuracy.
Implementation Method 1
resonance frequency change means for changing an electrical length between the pair of radio wave half mirrors to change a resonance frequency of a resonator formed between the pair of radio wave half mirrors
Implementation Method 2
a frequency conversion unit that mixes the output signal from the millimeter-wave band filter with a first local signal with a fixed frequency to convert the output signal into a signal in a second frequency band lower than the first frequency band
Data Source
AI summary
An input signal Sx in a first millimeter-wave frequency band higher than 100 GHz is input to a millimeter-wave band filter 20 in which a pair of radio wave half mirrors 30A and 30B so as to opposite to each other and which performs a resonance operation. A signal component Sa corresponding to the resonance frequency of the filter is extracted, is mixed with a first local signal L1 with a fixed frequency, and is converted into a signal in a second frequency band. The converted signal component Sb is mixed with a second local signal L2 whose frequency is swept and is converted into a signal in a predetermined intermediate frequency band. Then, the level of the signal is detected. The millimeter-wave filter 20 has high selectivity characteristics in a frequency domain higher than 100 GHz and can change its passband center frequency.