3D RF Emitter Geolocation Using UAV MSNR Selection
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Solution Overview
Problem
Conventional RF emitter geolocation techniques based on received signal strength (RSS) are inaccurate due to multipath fading and shadowing effects, requiring extensive data processing and terrain modeling, limiting their applicability.
Innovation Solution
A three-dimensional energy-based geolocation technique using small unmanned air vehicles (UAVs) that selects maximum signal to noise ratio (MSNR) measurements and employs a Least Mean Square (LMS) method to determine RF emitter locations, minimizing errors from path loss modeling and signal fading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If RSS-based geolocation technique is used, then the technique can be applied generally, but the accuracy is poor due to multipath fading and shadowing effects
Solution Approach 1:
The patent extracts and removes the harmful effects of multipath fading and shadowing by selecting only Line-of-Sight (LOS) signal measurements for geolocation processing. The system identifies and excludes non-LOS measurements that are corrupted by reflections and obstructions, thereby eliminating the source of measurement errors and improving geolocation accuracy.
Solution Approach 2:
The patent changes the measurement parameter from raw RSS values to signal-to-noise ratio (SNR) values. By transforming the measurement metric and applying SNR-based selection criteria, the system enhances the quality of measurements and improves robustness against fading and shadowing effects while maintaining general applicability.
2Measurement precision
If RF propagation map with terrain modeling is used, then the geolocation accuracy is improved, but the device complexity and computing capacity requirements increase
Solution Approach 1:
The patent extracts only the essential measurement data (SNR values from LOS measurements) needed for accurate geolocation, eliminating the need for complex terrain modeling and large-scale RF propagation maps. This extraction approach maintains geolocation accuracy while dramatically reducing system complexity and computing requirements.
Solution Approach 2:
The patent replaces expensive, complex terrain modeling systems with simple, lightweight SNR measurement and selection algorithms. The system uses basic measurement devices on mobile platforms rather than expensive fixed infrastructure, achieving comparable or better accuracy with much lower cost and complexity.
3Reliability
If multiple real-time measurements are collected, then the geolocation reliability is improved, but the loss of time and processing overhead increase
Solution Approach 1:
The patent extracts only the most reliable measurements (those with highest SNR and LOS conditions) from the measurement set, discarding redundant or low-quality data. This selective extraction approach maintains high geolocation reliability while minimizing the number of measurements needed and reducing processing time.
Solution Approach 2:
The patent applies a threshold-based selection criterion that processes measurements partially rather than exhaustively. By setting SNR thresholds and selecting only measurements above the threshold, the system achieves sufficient reliability without processing all available measurements, thereby reducing time loss and processing overhead.
Data Source
AI summary
According to an embodiment of the present invention, a three-dimensional (3-D) energy-based emitter geolocation technique determines the geolocation of a radio frequency (RF) emitter based on energy or received signal strength (RSS) of transmitted signals. The technique may be employed with small unmanned air vehicles (UAV), and obtains reliable geolocation estimates of radio frequency (RF) emitters of interest.