Object Tracking Beyond Radar Range With Multi-Node GPS
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Solution Overview
Problem
Current object tracking methods fail to track objects that are out of the radar's detection range, leading to potential collision risks.
Innovation Solution
An object tracking system and method that utilizes sensors, GPS data, and communication networks to determine relative position vectors and position variation vectors, enabling accurate tracking of objects beyond the radar's range by combining data from multiple nodes and performing double differentiation operations on GPS data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar detection is used to track objects, then tracking accuracy within detection range is improved, but objects beyond radar detection range cannot be tracked
Solution Approach 1:
The patent combines radar detection data with GPS position data from multiple nodes to track objects. When an object is detected by radar, its position is refined using radar measurements. When the object moves beyond radar range, the system continues tracking using GPS data from multiple nodes, merging these data sources to maintain continuous tracking capability across extended ranges while preserving accuracy where possible.
Solution Approach 2:
The patent introduces GPS positioning as an intermediary mechanism to bridge the gap between radar detection ranges. GPS data from multiple nodes serves as a mediator that enables continuous tracking of objects beyond radar detection range, allowing the system to maintain tracking capability without direct radar contact by using position data from other nodes in the network.
2Reliability
If multiple nodes and data sources are combined for tracking, then tracking range and reliability are improved, but system complexity increases
Solution Approach 1:
The patent divides the tracking system into independent nodes, each capable of autonomous operation with its own sensors and processors. Each node independently collects data from its local sensors (radar, GPS) and processes this data to contribute to the overall tracking solution. This segmentation allows the system to achieve high reliability through distributed operation while keeping individual node complexity manageable.
Solution Approach 2:
The patent designs each node to perform multiple functions: local object detection via radar, self-positioning via GPS, data processing, and communication with other nodes. This multi-functionality reduces the need for specialized dedicated components at each node, thereby reducing overall system complexity while maintaining reliability through redundant capabilities across multiple nodes.
Data Source
AI summary
An object tracking method and an object tracking system are provided. The method includes: obtaining a first relative position vector from a first node to a second node at a first time point; obtaining a first position data of the first node and a second position data of the second node at a second time point; identifying a position variation vector from the first node to the second node based on the first position data of the first node and the second position data of the second node; and identifying a second relative position vector from the first node to the second node at the second time point based on the first relative position vector and the position variation vector. The method improves the tracking accuracy.