Signal Detection Using Direction Finding Distribution Analysis
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Solution Overview
Problem
There is a need for efficient detection of weak or low probability of intercept signals, which are difficult to detect due to their weak nature or intentional characteristics that complicate their identification.
Innovation Solution
A method and apparatus that perform continuous direction finding in time-frequency intervals, determining the distribution of direction finding results to evaluate the existence of a signal source, using a histogram to identify the bearing and calculating a probability that the maximal number of direction finding results do not originate from noise, with the ability to detect signals across a 360° range divided into equidistant angle intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous direction finding is performed in time-frequency intervals to detect weak signals, then the detection capability for low probability of intercept signals is improved, but the processing complexity and computational load increase
Solution Approach 1:
The patent divides the detection process into discrete time-frequency intervals and angle intervals. The 360° angle range is segmented into multiple intervals, and signals are processed in specific time-frequency blocks. This segmentation allows the system to manage complexity by processing data in manageable chunks rather than handling the entire signal space at once, while maintaining comprehensive detection coverage.
Solution Approach 2:
The patent introduces a statistical evaluation dimension by calculating the distribution of direction finding results across angle intervals and computing probabilities using statistical formulas. This adds a probabilistic assessment dimension to the traditional directional detection, enabling the system to distinguish signal sources from noise through statistical significance testing rather than relying solely on signal strength thresholds.
2Adaptability or versatility
If the frequency range and time range are divided into multiple intervals for comprehensive search, then the detection coverage is improved, but the search time and processing duration increase
Solution Approach 1:
The patent segments both the frequency range and time range into multiple intervals, creating a grid of time-frequency blocks. This segmentation enables systematic processing of the entire search space while allowing the system to optimize the number of intervals based on computational resources and detection requirements. The segmentation also facilitates parallel processing of different time-frequency intervals.
Solution Approach 2:
The patent implements continuous direction finding across all time-frequency intervals, maintaining constant surveillance of the entire frequency and time range. This continuous processing ensures that no potential signal is missed while the systematic interval structure allows for efficient time management through predictable processing cycles and potential optimization of interval sizes based on signal characteristics.
3Measurement precision
If statistical evaluation is performed to distinguish signal from noise, then the detection accuracy is improved, but the computational requirements increase
Solution Approach 1:
The patent changes the evaluation parameter from raw signal strength to statistical probability values. By computing the probability that maximal direction finding results in a specific angle interval do not originate from noise, the system transforms detection into a statistical hypothesis testing problem. This parameter transformation enables more accurate discrimination between signals and noise while allowing for optimization of computational effort through statistical methods rather than exhaustive analysis.
Data Source
AI summary
The present application is related to a method for detection of a signal, the method comprising the steps of performing continuously a direction finding in time-frequency intervals within a time range and a frequency range, determining for each frequency interval a distribution of the direction finding results, DFRs, for all time intervals and evaluating the determined distribution of direction finding results, DFRs, to detect the existence of a signal emitted by a signal source.