Mobile Signalling Trajectory Reconstruction Under Antenna Hopping
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Solution Overview
Problem
Existing methods for determining trajectories from mobile device signalling events are unreliable, costly, lack contextual information, and are sensitive to antenna hopping, particularly in urban zones, leading to inaccurate trajectory data.
Innovation Solution
A device and method that refine trajectory data by grouping signalling events into movement and stop types, generating graphs for each group, computing the shortest path, and redefining segments based on the shortest path to enhance accuracy, while excluding links that exceed distance thresholds and managing antenna hopping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a high distance threshold is used to detect large movements, then wide vision is achieved, but small movements within stops are missed
Solution Approach 1:
The patent divides the trajectory into multiple segments based on stop type labels and movement type labels. By segmenting the trajectory data, the system can apply different distance thresholds to different segments - using a higher threshold for movement segments (wide vision) and a lower threshold for stop segments (precise vision), thus resolving the contradiction between detection coverage and measurement precision.
Solution Approach 2:
The patent dynamically adjusts the distance threshold based on the type of trajectory segment being analyzed. Instead of using a fixed threshold, the system adapts the threshold parameter according to whether the current segment is classified as movement or stop, allowing optimal detection parameters to be applied contextually throughout the trajectory.
2Measurement precision
If a low distance threshold is used to detect small movements, then precise vision is achieved, but noise is created due to antenna hopping
Solution Approach 1:
The patent applies preliminary processing to classify trajectory segments into stop and movement types before applying distance threshold filtering. By performing this classification in advance, the system can then apply appropriate thresholds to each segment type, preventing antenna hopping noise from being misinterpreted as genuine small movements while preserving actual precise movements.
Solution Approach 2:
The patent introduces trajectory segment classification as an intermediary step between raw signalling events and final trajectory determination. This intermediary classification layer acts as a filter that distinguishes genuine movement patterns from antenna hopping artifacts, allowing precise detection without noise contamination.
3Measurement precision
If trajectory data is refined by grouping signalling events and computing shortest paths, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the trajectory into movement and stop segments, and further divides movement segments into movement groups that can be processed independently. This segmentation allows the computationally intensive shortest path computation to be applied only to relevant movement groups rather than the entire trajectory, reducing overall processing complexity while maintaining precision.
Solution Approach 2:
The patent applies shortest path computation selectively to movement groups rather than uniformly to all trajectory segments. By applying this refined processing only where needed (in movement segments with multiple signalling events), the system achieves high measurement precision for critical portions while avoiding unnecessary computational overhead in stop segments.
Data Source
AI summary
The invention relates to a device for determining a trajectory arranged to receive mobile or wireless telephone network signalling events each comprising a mobile communication device identifier, a timestamp, and a signalling identifier associated with a location and with a location radius, and to return trajectory data comprising trajectory segments each comprising two timestamps forming boundaries based on the timestamps of the signalling events, each segment being associated with a movement type or stop type label.