Distributed Satellite Tracking Auctions for Multi-Target Coverage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing multi-target tracking systems face challenges in efficiently managing large satellite constellations to ensure comprehensive target coverage, adherence to satellite vehicle constraints, and handling dynamic target events while maintaining tracking accuracy and resource utilization.
Innovation Solution
An auction-based distributed optimization method is employed, where satellite vehicles in a constellation receive tracking information, compute reward values, communicate bids, and iteratively select winner vehicles to form an optimal team for target tracking, using a sequential single-item auction framework and max-consensus algorithm to handle tracking requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized tracking system is used to manage satellite constellations, then coordination and control are simplified, but the system becomes vulnerable to single points of failure and communication bottlenecks
Solution Approach 1:
The patent segments the centralized tracking system into multiple distributed satellite vehicles (SVs) that independently perform tracking functions. Each SV in the constellation acts as an autonomous node, eliminating the single point of failure inherent in centralized systems while maintaining coordinated multi-target tracking capabilities through distributed consensus algorithms.
Solution Approach 2:
Each satellite vehicle in the constellation autonomously computes its own bid based on its tracking capabilities and current state, then communicates this bid to neighboring SVs. This self-service approach eliminates the need for a centralized controller to manage all tracking decisions, reducing communication infrastructure complexity while improving system reliability.
2Reliability
If more satellite vehicles are deployed to ensure comprehensive target coverage, then tracking coverage and redundancy improve, but resource utilization efficiency and coordination complexity increase
Solution Approach 1:
The patent implements a dynamic auction-based framework where satellite vehicles iteratively update their bids based on current target states and resource availability. This dynamic approach allows the system to automatically adapt to changing conditions with multiple SVs, optimizing resource utilization efficiency while maintaining comprehensive tracking coverage without linearly increasing coordination complexity.
Solution Approach 2:
The sequential single-item auction framework incorporates feedback loops where each SV receives bid information from neighboring SVs, updates its own bid accordingly, and communicates the updated bid back to the network. This feedback mechanism enables efficient coordination among numerous SVs, ensuring comprehensive target coverage while preventing coordination complexity from becoming unmanageable.
3Productivity
If real-time tracking of multiple dynamic targets is implemented, then target detection capability improves, but computational load and communication bandwidth requirements increase
Solution Approach 1:
The patent extracts only the essential bid information (tracking capability and resource state) that each satellite vehicle needs to communicate with its neighbors, rather than exchanging complete state data. This extraction approach maintains real-time target detection capability across multiple SVs while significantly reducing communication bandwidth consumption and associated energy losses.
Solution Approach 2:
The system performs partial auctions sequentially for different targets rather than simultaneously processing all targets. This partial action approach allows real-time tracking of multiple dynamic targets by dividing the computational and communication load across time, maintaining high target detection capability while reducing peak communication bandwidth requirements.
4Speed
If satellite vehicles operate independently to reduce coordination overhead, then system responsiveness improves, but tracking accuracy and cooperative performance deteriorate
Solution Approach 1:
The patent implements preliminary bid computation at each satellite vehicle before the auction process begins. Each SV pre-calculates its tracking capability and resource state, allowing it to respond immediately when a target event is detected. This preliminary action maintains system responsiveness while enabling subsequent cooperative refinement of tracking accuracy through the auction framework.
Data Source
AI summary
An auction-based distributed method for cooperative multi-target tracking by a plurality of satellites, includes distributed target tracking error and utilization computation as an auction bid across the satellite and uses message-passing to find best bid, handles different tracking requirements via definition of bids and modification of task definition used during the bidding process, and selected a list of auction winners to track the target.