Autonomous UAV Target Tracking via Adaptive Sensor Orientation
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Solution Overview
Problem
Human operators must closely monitor imagery from UAVs to maintain a moving target within the sensor's field of view, which is inefficient and prone to errors in tracking, especially when target motion patterns are complex.
Innovation Solution
A system and method that use information about target location, UAV platform type, sensor payload capabilities, and target-to-UAV speed ratios to select sub-algorithms for generating desired platform positions and sensor orientation commands, enabling autonomous tracking by selecting from a suite of sub-algorithms for maintaining the target within the sensor's field of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators monitor imagery to maintain target in view, then target tracking reliability is improved, but operator workload increases and efficiency decreases
Solution Approach 1:
The system enables autonomous target tracking where the UAV automatically adjusts its position and orientation to maintain the target within the sensor field of view. The autonomous tracker receives target location data and autonomously computes platform positions and sensor orientations, eliminating the need for continuous human operator intervention while maintaining reliable tracking.
2Reliability
If human operators monitor imagery to maintain target in view, then target tracking reliability is improved, but time consumption increases
Solution Approach 1:
The autonomous tracking system continuously monitors target location and automatically adjusts platform position and sensor orientation without requiring operator attention. This self-service capability maintains reliable tracking while eliminating the time operators would spend manually monitoring and adjusting the view.
Solution Approach 2:
The system implements a feedback loop where the autonomous tracker continuously receives updated target location data, compares it with the current sensor field of view, and automatically computes corrective platform positions and sensor orientations to maintain the target in view, enabling rapid response to target motion.
3Ease of operation
If autonomous tracking is implemented, then operator workload is reduced, but system complexity increases
Solution Approach 1:
The autonomous tracker serves as a self-service module that automatically performs target tracking computations and generates control commands. It receives input data (target location, platform state, sensor capabilities) and autonomously determines platform positions and sensor orientations, reducing operator workload while managing system complexity through modular design.
Solution Approach 2:
The tracking system is segmented into distinct functional modules: the autonomous tracker that computes desired platform positions and sensor orientations, the platform that executes position changes, and the sensor that adjusts orientation. This segmentation manages complexity by dividing the autonomous tracking function into manageable, specialized components.
4Adaptability or versatility
If adaptive sub-algorithm selection is used, then tracking adaptability is improved, but computational complexity increases
Solution Approach 1:
The autonomous tracker dynamically selects from multiple sub-algorithms based on the specific tracking scenario and target motion patterns. This dynamic adaptation allows the system to optimize its tracking approach for different situations (e.g., maneuvering targets vs. stationary targets) while managing computational complexity through conditional logic rather than a single complex algorithm.
Data Source
AI summary
This invention provides a system and method for autonomously tracking a moving target from unmanned aerial vehicles (UAVs) with a variety of airframe and sensor payload capabilities so that the target remains within the vehicle's sensor field of view regardless of the specific target motion patterns. The invention uses information about target location, UAV platform type and states, sensor payload capability, and ratio of target-to-UAV speeds to select from a suite of sub-algorithms, each of which generates desired platform positions (in form of waypoints) and/or sensor orientation commands to keep the target in view.