A distributed passive MIMO radar joint target detection and localization method
By using an iterative update method based on the factor graph model of distributed passive MIMO radar, the computational complexity and direct wave interference problems of passive radar target detection algorithms are solved, achieving efficient target detection and localization.
CN117031428BActive Publication Date: 2026-06-19XIDIAN UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIDIAN UNIV
- Filing Date
- 2023-08-01
- Publication Date
- 2026-06-19
AI Technical Summary
Technical Problem
Existing passive radar target detection algorithms have high computational complexity in large grid and multi-sample scenarios, and cannot effectively suppress direct wave interference, resulting in poor real-time performance and detection results.
Method used
A distributed passive MIMO radar joint target detection and localization method is adopted. By establishing a unified model of the received signal, constructing a factor graph model, and iteratively updating it, the computational complexity is reduced and the anti-direct wave interference performance is improved.
Benefits of technology
It achieves efficient target detection and localization, reduces computational complexity, and maintains high detection performance in environments with strong direct wave interference.
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Smart Images
Figure CN117031428B_ABST
Abstract
This invention discloses a method for joint target detection and localization using distributed passive MIMO radar, comprising: acquiring discrete time-domain signals from a reference channel and a receiving channel; simultaneously introducing target state variables to establish a unified model for the received signals of the distributed passive radar; establishing a marginal probability estimation problem for unknown parameters in the joint target detection and localization using distributed passive MIMO radar, and constructing a factor graph model for joint target detection and localization using distributed passive MIMO radar; iteratively updating the message and confidence of each variable in the factor graph model to obtain the confidence of the target state variable and the confidence of the target position variable; obtaining a log-likelihood function based on the confidence of the target state variable, and obtaining a test threshold accordingly to achieve target detection; and simultaneously, achieving target localization based on the mean of the confidence of the target position variable. This method can reduce computational complexity, has high detection performance, and good resistance to direct wave interference.
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