Passive Radio Source Localization Using Wideband Time-of-Arrival
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Solution Overview
Problem
Existing methods for detecting unauthorized radio-emitting devices, such as drones, are inefficient due to the need to know the device in advance and rely on traditional radar, which struggles with low-density materials like polymers and require active detection.
Innovation Solution
A passive location-finding method using time-of-arrival techniques with multiple sensors, applying convex hull and cluster filters to determine the radio emission source's location without prior knowledge, utilizing wide-band receivers and correlation analysis to detect signals across a frequency range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional radar methods are used to detect drones, then detection capability is improved, but drones made from low-density materials cannot be reliably differentiated from birds
Solution Approach 1:
The patent replaces traditional radar (electromagnetic wave-based mechanical detection) with acoustic detection using microphones and signal processing. By detecting the acoustic signature of drone propellers and analyzing the radio frequency signals emitted by drones, the system achieves reliable detection and differentiation from birds without relying on radar reflections that fail for low-density materials.
Solution Approach 2:
The patent introduces radio frequency signal monitoring as an intermediary detection method. Instead of directly detecting the physical drone body with radar, the system detects the radio signals that drones emit for control and telemetry, providing an indirect but reliable detection pathway that works regardless of the drone's physical material composition.
2Reliability
If narrow-band receivers monitoring specific frequency ranges are used, then detection of known drone types is improved, but undetected or unknown drone types cannot be reliably detected
Solution Approach 1:
The patent employs wide-band receivers that can detect radio signals across a broad frequency spectrum, making the system universal and adaptable to various drone types regardless of their specific communication frequencies. This multi-functional capability allows the system to detect both known and unknown drone types without requiring prior characterization.
Solution Approach 2:
The system performs preliminary signal capture across wide frequency bands before analyzing specific signal characteristics. By first capturing all radio emissions in the environment and then processing them to identify drone signals, the system prepares for detection of any drone type without needing advance knowledge of the specific drone's frequency characteristics.
3Measurement precision
If signal processing is performed on all detected signals, then detection accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent applies different levels of signal processing to different detected signals based on their characteristics and relevance. Instead of uniformly processing all signals with the same complexity, the system selectively applies sophisticated analysis methods only to signals that show characteristics consistent with drone emissions, thereby maintaining high accuracy while reducing overall computational burden.
Solution Approach 2:
The system performs complete signal processing only on a subset of detected signals that are most likely to be drone signals, based on preliminary filtering criteria. By applying full analytical processing partially to selected signals rather than excessively to all signals, the system achieves high measurement precision for relevant targets while controlling computational complexity.
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
Enables accurate and efficient detection of radio emission sources by calculating possible positions and applying filters to refine estimates, providing precise location and bearing angles without prior knowledge of the emission source's frequency.
Implementation Method 1
Time-of-arrival methods, based on differences in transit time between an actively emitting object and a number of sensors
Data Source
Figure 1~2
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Figure 4~5
AI summary
A method for passively locating a radio emission source (2a, 2b) is described. The method includes including receiving radio signal datasets corresponding to each of three of more sensors (3). Each sensor includes at least one radio receiver. The method also includes receiving or retrieving a physical location corresponding to each sensor. The physical locations define a convex hull (5). The method also includes determining whether an emitter signal (8) within a target frequency range is present in any of the radio signal datasets, and assigning any radio signal dataset which comprises the emitter signal as a detection dataset. The method also includes, in response to determining three or more detection datasets, calculating a signal location based on arrival times of the emitter signal and the respective physical locations. The method also includes generating a locus of possible positions based on calculating two or more alternative signal locations.