Sub-channel FFT Signal Detection Reducing Interference False Positives
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Solution Overview
Problem
Existing signal detection systems are often confused by interfering signals of different modulation types, leading to false positives, particularly in the presence of wide-band or narrow-band interference such as thermal noise, spread-spectrum signals, and harmonics.
Innovation Solution
A method involving a sub-channel Fast Fourier Transform (FFT) is used to distinguish a signal of interest from interference by averaging FFT bin magnitudes over time, comparing the signal shape to reference patterns, and computing metrics to determine the presence of the signal of interest, while rejecting corrupted samples and applying filters to reduce pulsed interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional signal detection methods are used, then the system can detect signals, but it is confused by interfering signals leading to false positives
Solution Approach 1:
The patent divides the frequency spectrum into multiple sub-channels and performs FFT on each sub-channel separately. This segmentation allows the system to analyze different frequency components independently, making it easier to distinguish the signal of interest from interference signals that may be present in other sub-channels. The spectral shape is constructed by combining results from multiple sub-channels, providing a more robust detection mechanism.
Solution Approach 2:
The patent transforms the signal representation into the frequency domain using FFT, effectively changing the 'color' or domain of the signal from time-domain to frequency-domain. This transformation reveals the spectral shape characteristics that are not visible in the time domain, enabling the system to differentiate between signals with different modulation types even when they have similar power levels. The spectral shape acts as a unique identifier for different signal types.
2Adaptability or versatility
If the system attempts to detect all signal types, then coverage is improved, but complexity increases making it harder to distinguish signals from interference
Solution Approach 1:
The patent changes the parameter used for signal detection from simple power-level thresholding to spectral shape analysis. Instead of detecting signals based on their amplitude or power, the system analyzes the distribution of energy across frequency bins in the FFT spectrum. This parameter change allows the system to distinguish between different modulation types (e.g., spread-spectrum vs. narrowband) based on their characteristic spectral shapes, providing better adaptability without proportionally increasing complexity.
Solution Approach 2:
The patent replaces traditional mechanical or analog signal detection methods with digital signal processing techniques. Specifically, it uses digital FFT transformation and computational spectral shape analysis instead of analog filtering or thresholding circuits. This substitution enables more sophisticated analysis capabilities while maintaining flexibility through software-based implementation, allowing the system to adapt to different signal types through algorithmic changes rather than hardware reconfiguration.
Data Source
AI summary
A method for distinguishing a signal of interest from one or more interference signals in a received analog signal comprises receiving an analog signal at a radio front end, and transmitting the received analog signal to an analog-to-digital converter to sample data in the received analog signal and output a digital signal. A sub-channel Fast Fourier Transform (FFT) is performed on the digital signal, and sub-channel FFT bin magnitudes are averaged over a set period of time to determine a shape of the received signal. The shape of the received signal is compared to one or more signal reference patterns by computing a metric for the shape of the received signal, and computing a metric for the one more signal reference patterns. The computed metrics are then compared to a predetermined threshold value to determine the presence, or lack thereof, of a signal of interest in the received signal.