Distributed Sensor Network for Vehicle Localization in No-LOS Conditions
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Solution Overview
Problem
Current vehicle location and speed detection systems face challenges in accurately tracking vehicles in complex road geometries and environments with no direct path for radar and communication signals, such as winding roads and congested urban areas, which affects the reliability of automatic driving systems.
Innovation Solution
A distributed sensor network utilizing high-resolution subspace signals and MIMO antenna arrays in cellular stations to estimate the direction of arrival and time delay of vehicles, enabling accurate location and speed tracking through a low-latency wireless communication model, even in no-line-of-sight conditions, and integrating this data with V2X communication systems for real-time vehicle tracking and hazard detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar and communication signals are used for vehicle tracking in complex road geometries, then vehicle location and speed detection can be performed, but accuracy deteriorates in no-line-of-sight conditions such as winding roads and congested urban areas
Solution Approach 1:
The patent combines multiple sensing technologies (radar, communication signals, and distributed sensor network) into an integrated system. By merging these different sensing modalities, the system achieves reliable vehicle tracking in both line-of-sight and no-line-of-sight conditions, overcoming the limitations of individual technologies.
Solution Approach 2:
The distributed sensor network is designed to perform multiple functions: vehicle localization, speed estimation, and tracking in various geographic conditions. The system universally handles different road geometries including winding roads, congested urban areas, and no-line-of-sight scenarios through a unified approach using subspace signals.
2Measurement precision
If distributed sensor network with MIMO antenna arrays is deployed to improve tracking in no-line-of-sight conditions, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system divides the sensing function into distributed sensor nodes with MIMO antenna arrays positioned at multiple locations. Each node independently processes subspace signals and contributes to the overall vehicle tracking, allowing the complex function to be segmented across multiple simpler units.
Solution Approach 2:
The patent introduces subspace signals as an intermediary mechanism that enables information exchange and coordination between distributed sensor nodes. These high-resolution subspace signals facilitate accurate location approximation while managing the complexity of the distributed network through structured signal processing.
Data Source
AI summary
A system and method for vehicle-tracking and localization with a distributed sensor network is provided that includes a plurality of cellular station. A pilot signal is received from the vehicle with an arbitrary station. The pilot signal is compared to each vehicle profile with the arbitrary station in order to identify a matching profile. Spatial positioning data is received for the vehicle with the arbitrary station. The vehicle profile and the spatial positioning data is relayed from the arbitrary station to the at least one proximal station from the plurality of cellular stations. A plurality of iterations is executed. The spatial positioning data is compiled from each iteration into a predicted path for the vehicle with the cellular stations. A warning notification is sent from the arbitrary station of the current iteration to the vehicle, if the predicted path is intersected by at least one hazard.