Anti-eavesdropping distributed tracking detection method of target tracking system under low communication resource

By designing a time-varying distributed filter and encryption/decryption mechanism under low communication resource conditions, the problem of eavesdropping detection in target tracking systems is solved, achieving efficient target tracking and privacy protection, and improving the system's tracking accuracy and communication efficiency.

CN121188422BActive Publication Date: 2026-07-14HARBIN UNIV OF SCI & TECH
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Patent Information

Application Number
CN202511216712.1
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-08-28
Publication Date
2026-07-14
Estimated Expiration
2045-08-28

AI Technical Summary

Technical Problem

Existing technologies struggle to address the problem of eavesdropping prevention in distributed tracking and detection systems for target tracking systems that simultaneously employ periodic scheduling mechanisms and encryption/decryption mechanisms under low communication resource conditions, leading to a decrease in system estimation accuracy.

Method used

This paper proposes a distributed tracking and detection method for preventing eavesdropping in target tracking systems under low communication resource conditions. By establishing a stochastic dynamic model, designing a time-varying distributed filter, calculating the filter gain matrix and estimating the upper bound of the error covariance, and combining a periodic scheduling mechanism and an encryption/decryption mechanism, the filter gain matrix is ​​solved using a recursive matrix equation to prevent eavesdroppers from intercepting useful information.

Benefits of technology

The tracking performance of the target tracking system was improved, the tracking performance of the sensor node was satisfactory, the tracking error of the eavesdropper diverged, verifying the feasibility and effectiveness of the method, and improving the communication efficiency and privacy protection of the system.

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Abstract

The application provides a target tracking system anti-eavesdropping distributed tracking detection method under low communication resources, and belongs to the technical field of distributed tracking detection. The application establishes a random dynamic model of a target tracking system under low communication resources; then, a time-varying distributed filter under the least mean square error is designed according to the dynamic model; then, a filter gain matrix of each sensor node in the system at a time point is designed; the filter gain matrix is substituted into the filter to obtain the state estimation of each sensor node in the system at the time point; and the estimation error covariance upper bound of each sensor node in the system at the time point is calculated; let, and repeat until the condition is met. The application solves the problem that the existing distributed tracking detection method is difficult to simultaneously process the target tracking system anti-eavesdropping distributed tracking detection problem with a periodic scheduling mechanism and an encryption and decryption mechanism, thereby improving the tracking performance of the tracking system.
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