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Maneuvering multi-target tracking algorithm under dense clutter condition based on GPU architecture

A GPU architecture and multi-target tracking technology, which is applied in the field of mobile multi-target tracking algorithm under dense clutter conditions based on GPU architecture, can solve the problems of high clutter density and impossibility of real-time implementation, and achieve the effect of reducing the number of cycles

Inactive Publication Date: 2014-09-03
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

The main calculation amount of the IMM-JPDA algorithm is reflected in the acquisition of related events between targets and measurements, which will increase exponentially with the increase in the number of targets and measurements, that is, "combination explosion". , if there are many targets or high clutter density in the monitoring area, the IMM-JPDA algorithm cannot be implemented in real time at all

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  • Maneuvering multi-target tracking algorithm under dense clutter condition based on GPU architecture
  • Maneuvering multi-target tracking algorithm under dense clutter condition based on GPU architecture
  • Maneuvering multi-target tracking algorithm under dense clutter condition based on GPU architecture

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Embodiment Construction

[0084] The present invention proposes a processing method based on GPU architecture, and the specific implementation steps are as follows:

[0085] S1, initialize the IMM-JPDA algorithm parameters at the CPU end, as follows:

[0086] S101. Initialize various parameters of the observation environment, the parameters include: frequency observation variance, angle observation variance, distance observation variance, observation equation corresponding to frequency, angle and distance, false alarm probability, detection probability, clutter density, radar sampling interval , the covariance of each model, the threshold γ of the confirmation gate, the state vector of the trajectory at time k-1 under model j The covariance matrix corresponding to the trajectory at time k-1 under model j target i corresponds to the probability of model j

[0087] S102. Collect observation information and store it in the observation matrix Z, and store the number of observations received by the mo...

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Abstract

The invention belongs to the technical field of radar and sonar, and mainly relates to a method for achieving CJML-IMM-PDA, in particular to a method for achieving initialization and maintenance of multi-weak-target trajectories under a dense clutter condition based on a GPD architecture. The trajectories of the multiple excited weak targets under the conditions of the low signal to noise ratio and the high clutter can be quickly initialized and the successfully-initialized trajectories can be kept in a tracking state on a Visual studio of a software integrated development platform provided by Microsoft.

Description

technical field [0001] The invention belongs to the technical field of radar and sonar, and mainly relates to the realization method of combined joint maximum likelihood_interactive multi-model-probabilistic data association algorithm (CJML-IMM-PDA), specifically a kind of intensive The implementation method of initializing and maintaining multiple weak target trajectories under clutter conditions can be quickly initialized and maintained for excited multiple weak targets under low signal-to-noise ratio and high clutter conditions on the software integrated development platform Visual studio provided by Microsoft. Keep track of successfully initialized trajectories. Background technique [0002] The multi-weak target tracking under dense clutter conditions has always been a research focus and difficulty in the field of multi-target tracking technology, and this technology plays a pivotal role in radar (sonar) systems. When the target clutter density in the detection area is...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T1/20G06T7/20
Inventor 唐续高林金辉李立萍
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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