Networked RF Sensor Fusion for Direction Finding Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current direction finding (DF) and geolocation (GEO) techniques for radio frequency (RF) emitters face challenges in accuracy due to errors from multi-path propagation, shadowing, fading effects, and channel irregularities, which are exacerbated by the need for precise antenna alignment and processing of energy-based measurements.
Innovation Solution
The System of Systems (SoS) DF-GEO approach leverages a network of RF sensors to share and process energy measurements from both omnidirectional and directional antennas, using Least Mean Square Error (LMSE) methods to compute geolocation data, optimizing performance by combining on-board and off-board processing resources and situational awareness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If energy-based DF/GEO methods are used, then the approach is more robust when emitter signal characteristics are unknown, but measurement precision deteriorates due to multi-path propagation, shadowing, and fading effects causing up to ±10 dB RMS path loss variations
Solution Approach 1:
The patent combines multiple RF sensors into a networked system where each sensor contributes energy measurements. By merging data from multiple spatial locations, the system achieves both robustness to unknown signal characteristics and improved measurement precision through cooperative processing and error mitigation.
Solution Approach 2:
The system implements iterative processing where initial geolocation estimates are refined through multiple passes of data processing. The networked sensors continuously exchange measurements and update their estimates, using feedback from the collective data to improve precision while maintaining adaptability to unknown signal characteristics.
2Measurement precision
If traditional DF/GEO systems use arrays of spatially displaced antennas, then DOA calculation is possible, but device complexity increases due to requirements for special antennas, close-tolerance amplitude/phase RF receiver components, enhanced receiver dynamic range, and expanded processing bandwidth
Solution Approach 1:
The patent divides the DF/GEO function across multiple independent RF sensors in a network, where each sensor uses simple one- or two-antenna configurations. This segmentation eliminates the need for complex multi-element arrays at each location, reducing device complexity while maintaining DOA calculation capability through cooperative processing of energy measurements from multiple sensors.
Solution Approach 2:
The system replaces physical antenna arrays with complex mechanical/electrical components with a networked system using simple antennas and energy-based measurements. By substituting the mechanical complexity of precision antenna arrays with computational complexity in the data processing network, the system achieves DOA calculation with simpler hardware.
3Measurement precision
If multiple signal processors are used to compare amplitude/energy, phase, and TOA/TDOA from various signals, then DOA and location can be derived, but processing time and computational resources increase
Solution Approach 1:
The patent extracts and utilizes only energy/RSS measurements from the signal, discarding the need to process amplitude/phase relationships and TOA/TDOA calculations. By taking out just the energy-based component, the system reduces processing time and computational resources while maintaining location derivation accuracy through the networked sensor approach.
Solution Approach 2:
The system uses a partial approach by relying solely on energy measurements rather than fully processing all signal characteristics (amplitude, phase, TOA, TDOA). This partial action reduces computational burden and processing time while the networked architecture provides sufficient data redundancy to maintain measurement precision.
Data Source
AI summary
Systems and methods are provided herein that extend well-known direction finding (DF) and geolocation (GEO) concepts and approaches to a plurality of RF sensors to form a System of Systems (SoS) DF-GEO approach. The RF sensors may be collocated or spatial separated, and are able to exchange or share DF/GEO data. The SoS DF-GEO approach opportunistically leverages both on-board and off-board processing resources and DF-GEO measures for cooperative processing, situation awareness sharing, and performance optimization. The off-board processing resources and DF-GEO measures may be shared via networking. Thus, the SoS DF-GEO approach primarily bases measurements upon RSS or energy obtained from a one-antenna system or from a two-antenna system of a single RF sensor, as well as from other RF sensors via networking. By adopting the innovative SoS DF-GEO concept approach as described herein, optimized DF-GEO performance can be obtained by using the system of systems approach.