Distributed Sensor Tracking Using Transect Fusion Across Coverage Gaps
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Solution Overview
Problem
Existing systems face challenges in accurately tracking and predicting the movement of objects using distributed sensors due to intermittent signal capture and limited sensor coverage, especially in non-overlapping fields of view.
Innovation Solution
A network of sensors mounted on fixed objects like light poles uses multi-channel microphone arrays and optical sensors to determine the angle of arrival and relative speed of moving objects, correlating observations with a map of sensor fields to predict object tracks through angular parallax motion and transect analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If distributed sensors are used to track objects, then coverage area is increased, but measurement precision deteriorates due to intermittent signal capture and limited sensor coverage
Solution Approach 1:
The patent merges discrete transect tracks from multiple distributed sensors into continuous motion paths through data fusion. By combining observations from multiple sensors that detect the same object at different locations and times, the system creates continuous tracking trajectories that overcome the intermittent nature of individual sensor measurements, thereby maintaining measurement precision across expanded coverage areas
Solution Approach 2:
The system performs preliminary correlation of sensor observations with predicted object tracks before final track determination. By pre-processing and correlating raw sensor data with expected motion patterns, the system prepares refined measurements in advance, enabling accurate object tracking even when individual sensor captures are intermittent or limited
2Device complexity
If discrete sensor observations are used, then device complexity is reduced, but reliability of continuous tracking deteriorates
Solution Approach 1:
The patent transforms discrete, intermittent sensor observations into continuous tracking information through the merging of transect tracks. By systematically combining data points from multiple discrete sensor events that occur at different times and locations, the system creates uninterrupted motion paths, ensuring continuous and reliable object tracking without requiring complex real-time monitoring infrastructure at every location
Solution Approach 2:
The system introduces an intermediary processing layer that correlates sensor observations with predicted tracks and merges discrete transects into continuous paths. This intermediary data fusion process acts as a mediator between simple discrete sensor inputs and reliable continuous tracking outputs, enhancing tracking reliability while maintaining relatively simple sensor device architecture
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
This approach enhances the accuracy and predictability of object tracking by merging discrete transect tracks into continuous motion paths, refining signal measurements, and providing forward alerts for applications like object interdiction and automated vehicle control.
Implementation Method 1
determine the angle of arrival and relative speed of moving objects, correlating observations with a map of sensor fields to predict object tracks through angular parallax motion
Implementation Method 2
uses multi-channel microphone arrays and optical sensors to determine the angle of arrival and relative speed of moving objects
Data Source
AI summary
A sequence of motion observations of a moving object are received from a first set of sensors. A first sequence of distance ratios are calculated based on the first sequence of motion observations. First transects are generated based on the first sequence of distance ratios. A first motion track of the moving object is produced based on: the first transects; and a map. A second set of sensors are determined employing the map. A second sequence of motion observations of the moving object are received from the second set of sensors. A second sequence of distance ratios for second pairs of the second set of sensors based on the second sequence of motion observations. Second transects are generated based on the second sequence of distance ratios. A second motion track is produced based on the first motion track, the second transects, and the map.