Yunyoung Kim’s scientific contributions

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Publications (2)


FIGURE 2. GPU memory allocation for CUDA kernel use.
FIGURE 3. Flowchart of parallelized model propagation using integrated kernels in PF algorithm.
FIGURE 4. Random values generated in CUDA Kernel 1 are shown in Fig. 3. We define it as the number of particles and store the generated random value in each tid.
FIGURE 11. Estimated target downrange compared to downrange calculated by radar measurements and true position.
FIGURE 12. Estimated target cross range compared to cross range calculated by radar measurements and true position.

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Accelerated Particle Filter With GPU for Real-Time Ballistic Target Tracking
  • Article
  • Full-text available

January 2023

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87 Reads

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4 Citations

IEEE Access

Daeyeon Kim

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Yunho Han

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Heoncheol Lee

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[...]

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Wonseok Choi

This study addresses the problem of real-time tracking of high-speed ballistic targets. Particle filters can be used to overcome the nonlinearity of motion and measurement models in ballistic targets. However, applying particle filters (PFs) to real-time systems is challenging since they generally require a significant computation time. So, most of the existing methods of accelerating PF using a graphics processing unit (GPU) for target tracking applications have accelerated computation weight function and resampling part. However, the computational time per part varies from application to application, and in this work, we confirm that it takes a lot of computational time in the model propagation part and propose accelerated PF by parallelizing the corresponding logic. The real-time performance of the proposed method was tested and analyzed using an embedded system. And compared to conventional PF on the central processing unit (CPU), the proposed method shows that the proposed method significantly reduces computational time by at least 10 times, improving real-time performance.

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Works related to the acceleration of PD-IPM.
The computation time for each part of PD-IPM.
The computation time for each process of construct modified KKT condition.
The computation time comparison results of the construct modified KKT condition part.
The computation time comparison results of the entire application.
GPU-Accelerated PD-IPM for Real-Time Model Predictive Control in Integrated Missile Guidance and Control Systems

June 2022

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63 Reads

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12 Citations

Sensors

This paper addresses the problem of real-time model predictive control (MPC) in the integrated guidance and control (IGC) of missile systems. When the primal-dual interior point method (PD-IPM), which is a convex optimization method, is used as an optimization solution for the MPC, the real-time performance of PD-IPM degenerates due to the elevated computation time in checking the Karush–Kuhn–Tucker (KKT) conditions in PD-IPM. This paper proposes a graphics processing unit (GPU)-based method to parallelize and accelerate PD-IPM for real-time MPC. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional PD-IPM and other methods showed that the proposed method improved the real-time performance by reducing the computation time significantly.

Citations (2)


... The challenges posed by these factors are addressed, and effective solutions to enhance the efficiency and accuracy of ballistic target tracking using particle filters are proposed in this paper. Most research has largely focused on the acceleration of Particle Filters using Graphics Processing Units (GPUs) [7], [8], [9]. Significant results in terms of increased computational speed have been yielded by this approach, but it causes the problem of power consumption [10]. ...

Reference:

Parallelized Particle Filter With Efficient Pipelining on FPGA for Real-Time Ballistic Target Tracking
Accelerated Particle Filter With GPU for Real-Time Ballistic Target Tracking

IEEE Access

... Given the high reliability requirements of designing missile control systems, traditional missile control system designs largely incorporate fixed supplementary and feedback techniques, which either control the missile system through frequency or provide structural analysis within the feedback frequency loop. With the development of theory, literature has shown that the concept of missile control system, which combines modern control theory and methods, gradually permeates into various aspects of missile autopilot design, guidance mode design, and so on (Lee et al. 2022). In order to comprehensively analyze the aviation capabilities of aviation guided missiles, such as pole configuration, variable structure control, and so on. ...

GPU-Accelerated PD-IPM for Real-Time Model Predictive Control in Integrated Missile Guidance and Control Systems

Sensors