UAV Directional Antenna Alignment via RSSI Feedback
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Solution Overview
Problem
Current UAV-to-UAV communication systems using directional antennas face challenges in achieving robust and long-distance communication due to imperfect communication environments and limited onboard sensing devices, which complicates the automatic alignment of directional antennas.
Innovation Solution
An improved aerial communication system employing a reinforcement learning-based directional antenna control algorithm that optimizes antenna headings for maximum received signal strength indicator (RSSI) in real-time, utilizing a unified communication channel for application and control data, and integrating Robot Operating System (ROS) for data transmission and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If directional antennas are used for UAV-to-UAV communication, then communication distance is extended and power consumption is reduced, but automatic alignment becomes difficult due to imperfect communication environments and limited sensing devices
Solution Approach 1:
The patent implements a feedback mechanism where the receiving UAV measures the received signal strength indicator (RSSI) and transmits this information back to the transmitting UAV. The transmitting UAV uses this RSSI feedback to iteratively adjust its antenna heading angle, selecting the angle that maximizes the received signal strength. This closed-loop feedback system enables automatic alignment without requiring complex sensing devices or perfect communication environments.
Solution Approach 2:
The patent employs a grid search algorithm that preliminarily scans multiple discrete heading angles to identify the optimal direction before fine-tuning the alignment. This preliminary action of scanning predefined angle grids allows the system to quickly establish an initial alignment direction, reducing the complexity of real-time continuous adjustment and enabling automatic alignment in resource-constrained UAV environments.
2Object-generated harmful factors
If directional antennas are used for UAV-to-UAV communication, then communication interference is reduced, but automatic alignment complexity increases due to unknown communication environments
Solution Approach 1:
The patent uses a grid search algorithm that evaluates a discrete set of heading angles rather than continuously optimizing the angle. This partial action approach scans through predefined angle increments (e.g., 5-degree steps) to identify the optimal direction, which simplifies the control algorithm complexity while still achieving sufficient alignment accuracy for reducing communication interference in UAV-to-UAV scenarios.
Solution Approach 2:
The system implements self-service alignment where each UAV independently performs its own antenna alignment based on RSSI feedback received from the other UAV. The transmitting UAV autonomously adjusts its own antenna heading without requiring external intervention or complex coordinated control algorithms, thereby reducing overall system complexity while effectively minimizing communication interference through proper directional alignment.
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
The system achieves robust and efficient long-distance UAV-to-UAV communication with reduced interference and power consumption, enabling on-demand broadband communication in emergency scenarios without relying on ground infrastructure, as verified through simulation studies and field tests.
Implementation Method 1
the use of directional antennas allows the energy to focus along a certain direction
Implementation Method 2
optimizes antenna headings for maximum received signal strength indicator (RSSI) in real-time
Data Source
AI summary
The present disclosure presents aerial communication systems and methods. One such system comprises an unmanned aerial vehicle platform and a communication component integrated with the unmanned aerial vehicle platform, wherein the communication component is configured to establish an Air to Air (A2A) communication channel with a remote directional antenna that is integrated with a remote unmanned aerial vehicle platform. The system further includes a computing component integrated with the unmanned aerial vehicle platform, wherein the computing component is configured to determine an optimal heading angle for transmission of communication signals from a directional antenna to the remote directional antenna in an unknown communication environment from received signal strength indicator (RSSI) information obtained from the remote directional antenna. Other systems and methods are also disclosed.