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.

CN122260307APending Publication Date: 2026-06-23NAVAL AVIATION UNIV
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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

Technical Problem

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.

Method used

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.

Benefits of technology

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.

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Abstract

The application belongs to the technical field of sensor data processing, and relates to a complex maneuvering weak multi-target detection and tracking method under range ambiguity, which is used for solving the prominent problem of coupling of target actual motion model mismatch, target maneuvering and range measurement ambiguity when complex maneuvering weak targets are detected and tracked, achieving coarse detection of weak multi-targets through noise reduction by sparse representation, introducing a target maneuvering variable into a target state under a delta-GLMB filter, constructing a pulse interval number increment tracking model, designing a multi-target fuzzy likelihood function, and realizing fine tracking of complex maneuvering weak multi-targets under range ambiguity, so that the limitation of application of an existing PHD filter method is overcome, and the method has strong engineering application value and promotion prospect.
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