Asynchronous Sensor Track Fusion via Interactive Multiple Model Filter
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Solution Overview
Problem
Current tracking applications in airspace are limited in accurately describing the motion of objects, such as drones, and fail to capture the complete dynamics of target objects, leading to reduced accuracy and effectiveness in preventing airspace collisions.
Innovation Solution
The system employs an interactive multiple model filter (IMMF) that processes signals from multiple sensors using different motion models, such as constant velocity and constant acceleration models, to fuse asynchronous sensor tracks and provide a single, accurate state estimate and error covariance for tracking objects in airspace.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single motion model is used in tracking applications, then the system complexity is reduced, but the accuracy of describing object motion deteriorates when targets maneuver or accelerate
Solution Approach 1:
The patent divides the tracking system into multiple parallel filters, each implementing a different motion model (e.g., constant velocity, constant acceleration, maneuvering models). Each filter processes sensor measurements independently to generate track estimates, allowing the system to handle diverse target dynamics without requiring a single complex model that would increase overall system complexity.
Solution Approach 2:
The patent changes the motion model parameters dynamically by selecting different models based on target behavior characteristics. When targets maneuver or accelerate, the system switches to appropriate motion models (e.g., from constant velocity to constant acceleration or maneuvering models), thereby maintaining high measurement precision without permanently increasing system complexity.
2Measurement precision
If multiple sensors with different motion models are used, then the accuracy of tracking objects over wide dynamics is improved, but the complexity of fusing asynchronous sensor tracks increases
Solution Approach 1:
The patent performs preliminary time alignment of asynchronous sensor tracks before fusion by propagating track estimates to a common time reference using the respective motion models. This preliminary action eliminates time synchronization issues, allowing subsequent fusion operations to proceed with standard algorithms without dealing with asynchronous data, thereby reducing overall fusion complexity.
Solution Approach 2:
The patent introduces a time alignment mechanism as an intermediary step between sensor data collection and track fusion. By using motion models to propagate tracks to a common time reference, the system creates a standardized interface that simplifies the fusion process, allowing multiple sensors with different sampling rates and processing speeds to be integrated without increasing fusion complexity.
3Ease of operation
If current tracking applications are used, then the system operation is simple, but the ability to capture complete dynamics of target objects deteriorates
Solution Approach 1:
The patent implements dynamic track management where the system automatically activates different motion models based on target behavior. When targets maneuver or accelerate, the system dynamically switches to appropriate models (e.g., from simple constant velocity to more complex maneuvering models), ensuring reliable collision prevention while maintaining simple operation through automatic model selection rather than manual intervention.
Data Source
AI summary
An example method can include receiving, at a sensor, a signal associated with a motion of a target, processing the signal via a first filter having a first motion model and a second filter having a second motion model to yield a first tracking output and a second tracking output for the target, and weighting the first tracking output and second tracking output according to how well each of the first motion model and second motion model represents the motion of the target, to yield a first weight for the first tracking output and a second weight for the second tracking output. The method can include combining the first tracking output and second tracking output to yield a fused tracking output and sending, to a fusion system, the fused tracking output, the first weight associated with the first tracking output and the second weight associated with the second tracking output.