Perception system based on multi-sensor data interaction verification

By adopting information entropy quantization and game theory optimization models in the multi-sensor perception system, the problems of multi-sensor data consistency verification and exception processing are solved, and high consistency and high reliability perceived data processing is achieved to adapt to the needs of complex environments.

CN119720078APending Publication Date: 2025-03-28INNER MONGOLIA UHV BRANCH OF STATE GRID INNER MONGOLIA EASTERN ELECTRIC POWER CO LTD +1
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Patent Information

Application Number
CN202411752522.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-02
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

Existing multi-sensor perception systems have technical bottlenecks in data consistency verification, abnormal data processing and global optimization, and cannot meet the requirements for system real-time and reliability in high-complex environments.

Method used

The multi-sensor data interaction verification perception system is adopted, including data preprocessing module, entropy calculation module, data optimization module, data interaction module, data reconstruction module and output module. Through information entropy, data uncertainty is quantified, and the game theory optimization model is combined to realize the interactive optimization of multi-sensor data, dynamically adjust the sensor output strategy, and improve the overall consistency and reliability of perceived data.

Benefits of technology

It effectively solves the problem of data inconsistency caused by sensor performance differences or environmental interference acquisition, improves the overall consistency and reliability of perceived data, adapts to complex perceived environments, and maintains high robustness and adaptability.

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Abstract

The invention relates to the field of multi-sensor sensing, and discloses a multi-sensor-based data interaction verification sensing system which comprises a data preprocessing module, an entropy calculation module, a data optimization module, a data interaction module, a data reconstruction module and an output module. The data preprocessing module preprocesses original data input by multiple sensors; the entropy calculation module quantifies the uncertainty of the single sensor data based on the information entropy theory and calculates the consistency of the overall data; the data optimization module optimizes a sensor output strategy; the data interaction module marks abnormal data in combination with marginal verification and joint verification methods; the data reconstruction module complements or replaces the abnormal data; and the output module integrates the reconstructed data and the normal data, completes consistency verification and then outputs the data to an upper-layer system. According to the method, efficient consistency verification and optimized output of multi-sensor data are realized, and the method can be widely applied to the fields of automatic driving, robot navigation, industrial monitoring and the like.
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