Frequency Envelope Detection for Fiber Optic Intrusion
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Solution Overview
Problem
Physical fiber optic intrusion detection systems face challenges in distinguishing between ambient signals and actual intrusion attempts, as ambient signals can overwhelm the system and reduce its sensitivity.
Innovation Solution
The implementation of a signal monitoring method using a Fourier Transform algorithm to create a Frequency Envelope, which adjusts sensitivity by applying a constant delta to frequency amplitude elements, and optionally employs a 'leaky bucket' algorithm to differentiate between ambient and intrusion signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simple threshold detection is used to monitor fiber optic signals, then the system operation is simple, but the system sensitivity is overwhelmed by ambient signals
Solution Approach 1:
The detection algorithm is segmented into multiple processing stages: Fourier Transform to convert time-domain signals to frequency-domain, envelope detection to extract amplitude characteristics, and multi-threshold comparison to distinguish intrusion from ambient signals. This segmentation allows complex signal processing to be broken down into manageable steps that improve sensitivity without overwhelming system complexity
Solution Approach 2:
The system transitions from simple time-domain threshold detection to frequency-domain analysis by applying Fourier Transform. This dimensional change from time to frequency domain enables the system to separate ambient periodic signals from intrusion signals based on their frequency characteristics, significantly improving measurement precision while maintaining manageable computational complexity
2Reliability
If the system monitors all signal variations to detect intrusions, then detection coverage is comprehensive, but ambient periodic signals overwhelm the detection capability
Solution Approach 1:
The system extracts the envelope of the frequency-domain signal to isolate the amplitude modulation characteristics from the raw signal. This extraction process separates the meaningful intrusion information from the ambient noise, allowing the system to focus on envelope variations that indicate intrusions while filtering out periodic ambient interference
Solution Approach 2:
The frequency envelope acts as an intermediary between the raw optical signal and the threshold comparison logic. By introducing this intermediate representation, the system can effectively separate intrusion signals from ambient periodic signals, as the envelope detection process naturally suppresses periodic components while preserving aperiodic intrusion signatures
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
This approach enhances the system's sensitivity to detect intrusion events while effectively rejecting ambient signals, ensuring accurate detection by adjusting thresholds and using a 'leaky bucket' mechanism to manage noise and perturbations.
Implementation Method 1
using a Fourier Transform (FT) algorithm to transform each piece of the stream into a three dimensional dataset including frequency domain amplitude, frequency and time
Data Source
AI summary
A signal which varies over time is monitored to determine an alarm condition, where the sample stream of digital values from an A/D converter is divided in to equal length pieces and a Fourier Transform (FT) algorithm is used to transform each piece of the stream into a three dimensional dataset including frequency domain amplitude, frequency and time. A Frequency Envelope is calculated by taking the maxima over the time dimension for a period of time, leaving a two dimensional frequency domain amplitude vs frequency dataset which is compared with new data arriving to determine the alarm condition for each element of the Frequency Envelope either by applying a constant delta additively or multiplicatively or by using a “leaky bucket” algorithm.