Distributed RF Positioning via Joint Waveform and Kalman Filtering
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Solution Overview
Problem
Modern radio frequency (RF) communication systems face challenges in efficiently managing limited spectral resources and reducing interference in congested environments, particularly in supporting high-density networks for vehicles like aircraft and unmanned aerial systems (UASs).
Innovation Solution
A distributed RF communications system that employs a joint waveform for simultaneous positioning and communication tasks, using adaptive filtering and Kalman filtering algorithms to iteratively track parameters and synchronize clocks, while leveraging sensors like GPS and INS for improved estimation processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple RF devices are deployed in high-density networks to support more users, then the number of supported users increases, but spectral congestion and interference increase
Solution Approach 1:
The patent combines positioning and communication functions into a single RF signal exchange process. The same RF signals used for communication also carry positioning information, eliminating the need for separate positioning infrastructure and reducing overall spectral demand while supporting high-density user networks
Solution Approach 2:
The RF signals perform multiple functions simultaneously - both communication data transmission and positioning estimation. This multi-functionality allows the system to support more users without proportionally increasing spectral resources, as each signal serves dual purposes
2Reliability
If traditional separate positioning and communication systems are used, then each system can be optimized independently, but spectral resources are consumed more efficiently and interference increases
Solution Approach 1:
The patent merges separate positioning and communication systems into a unified RF convergence architecture. By combining these functions, the system reduces total spectral consumption while maintaining the reliability benefits of independent optimization through joint processing algorithms
3Measurement precision
If estimation processes are performed in distributed RF systems, then positioning accuracy is achieved, but error propagation occurs across the network
Solution Approach 1:
The patent implements iterative tracking of position parameters using feedback mechanisms. The system continuously refines position estimates by feeding back measurement results and adjusting subsequent estimations, which helps correct errors and prevent their propagation across the distributed network
Solution Approach 2:
The system dynamically adjusts estimation parameters and tracking filters based on observed error characteristics. By changing parameters such as filter coefficients and tracking thresholds, the system maintains positioning accuracy while minimizing error propagation effects in the distributed network
Data Source
AI summary
Position information estimation in a distributed radio frequency (RF) communications system is provided. Embodiments disclosed herein facilitate high-precision estimations of positions, orientations, velocities, and acceleration of network nodes in a distributed RF network. The distributed RF communications system incorporates a series of estimation processes which makes it susceptible to propagation of errors. To ensure robustness of the distributed RF communications system, relative positions of network nodes are tracked by iteratively tracking parameters used for estimating position information. Some embodiments take advantage of Kalman filtering algorithms by leveraging principles directed by physics. At every network node, several filtering algorithms can be employed to synchronize clocks, track delay between multiple-input multiple-output (MIMO) antennas and estimate position and orientation of other network nodes. Information from other sensors like global positioning system (GPS) and inertial navigation system (INS) can also be employed to further improve estimation processes.