基于RZNN模型的TDOA和AOA移动目标定位方法
By using TDOA and AOA localization methods based on the RZNN model, the problems of nonlinearity and computational complexity in traditional localization technologies are solved, achieving high-precision and fast localization in noisy environments, and possessing global convergence and robustness.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- GUANGDONG OCEAN UNIVERSITY
- Filing Date
- 2026-01-08
- Publication Date
- 2026-07-17
AI Technical Summary
In TDOA and AOA positioning estimation, existing technologies suffer from nonlinearity, high computational complexity, poor real-time performance, and large angle estimation errors due to factors such as Doppler effect and antenna array phase mismatch, making it difficult to achieve high-precision real-time positioning.
An RZNN-based approach is adopted, which establishes dynamic equations for TDOA and AOA, performs equivalent linear transformations, and introduces a polynomial noise compensation term and a nonlinear logarithmic mapping activation function to construct an RZNN model. This model solves the localization problem in real time, suppresses high-order time-varying noise interference, and improves localization accuracy and robustness.
It achieves high-precision, low-latency, and highly stable positioning in complex noisy environments, possesses global convergence capability, and improves positioning accuracy and computational efficiency.
Smart Images
Figure CN121899752B_ABST