Complex maneuvering weak multi-target detection and tracking method under range ambiguity
By using the δ-GLMB filter and the pulse interval increment tracking model, the problems of target motion model mismatch and distance measurement ambiguity in PHD filtering technology are solved, and accurate tracking and robust detection of complex maneuvering weak multi-targets are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NAVAL AVIATION UNIV
- Filing Date
- 2026-05-28
- Publication Date
- 2026-06-23
AI Technical Summary
Existing PHD filtering techniques suffer from target motion model mismatch and distance measurement ambiguity coupling when dealing with complex maneuvering weak multi-target detection, leading to decreased tracking accuracy and increased computational complexity.
A pulse interval incremental tracking model based on the δ-GLMB filter and Markov criterion is adopted. Through sparse representation and subspace tracking algorithm, a three-dimensional energy distribution map of range-Doppler-azimuth is constructed to extract coarse target measurement data. Particle weights are updated and cluster analysis is performed under the δ-GLMB filter framework to achieve fine tracking of maneuvering multi-targets.
It effectively reduces the false alarm rate and enables precise tracking of weak multi-target maneuvers under ambiguous ranging conditions, overcoming the limitations of traditional methods and improving the accuracy and computational efficiency of target detection.
Smart Images

Figure CN122260307A_ABST