• 대한임베디드공학회논문지
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• 제17권6호
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• pp.355-365
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• 2022

This paper addresses the problem of real-time tracking a high-speed ballistic target. Particle filters can be considered to overcome the nonlinearity in motion and measurement models in the ballistic target. However, it is difficult to apply particle filters to real-time systems because particle filters generally require much computation time. This paper proposes an accelerated particle filter using graphics processing unit (GPU) for real-time ballistic target tracking. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional particle filter on CPU (central processing unit) showed that the proposed method improved the real-time performance by reducing computation time significantly.

• Journal of Astronomy and Space Sciences
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• 제29권4호
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• pp.363-374
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• 2012

This paper studies the problem of tracking a re-entry vehicle (RV) in order to predict its impact point on the ground. Re-entry target dynamics combined with super-high speed has a complex non-linearity due to ballistic coefficient variations. However, it is difficult to construct a database for the ballistic coefficient of a unknown vehicle for a wide range of variations, thus the reliability of target tracking performance cannot be guaranteed if accurate ballistic coefficient estimation is not achieved. Various techniques for ballistic coefficient estimation have been previously proposed, but limitations exist for the estimation of non-linear parts accurately without obtaining prior information. In this paper we propose the ballistic coefficient ${\beta}$ model-based interacting multiple model-extended Kalman filter (${\beta}$-IMM-EKF) for precise tracking of an RV. To evaluate the performance, other ballistic coefficient model based filters, which are gamma augmented filter, gamma bootstrapped filter were compared and assessed with the proposed ${\beta}$-IMM-EKF for precise tracking of an RV.

• 한국군사과학기술학회지
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• 제8권3호
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• pp.24-32
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• 2005

This paper describes the tracking filter performance for Naval Gun Ballistic Computation Unit(BCU). BCU needs tracing filter for gun firing. Using data of tracking sensor, BCU calculates the future position of Target and Gun order in the time of flight. In this paper, tracing filter is designed with interacting multiple model(IMM). The tracking algorithm based on the IMM requirers a considerable number of sub-model for the various maneuvering target in order to have a good performance. But, in the case of ship target, the maneuvering is restricted compared with the air target. Considering the maneuvering properties and adjusting the mode transition probabilities and the process noise of sub-model, We designed the IMM3 algorithm for Naval tracking filter with three sub-model.

• 한국전자파학회논문지
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• 제23권8호
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• pp.995-1001
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• 2012

본 논문에서는 다기능 레이더를 이용한 탄도탄 추적을 위해 알파-베타 필터, 칼만 필터, 탄도탄 추적 필터의 성능을 분석하였다. 제시된 필터들은 탄도탄의 궤적과 다기능 레이더의 신호처리기를 모의하는 시뮬레이터를 기반으로 시뮬레이션 되었다. 그 결과, 제안한 탄도탄 추적 필터의 성능이 알파-베타 필터에 비해 최대 75.3 %의 속도 오차 감소 효과가 있음을 확인하였다. 또한, 추적 초기화 이후에 제안한 필터가 칼만 필터보다 거리, 속도 오차가 작아 안정적인 성능을 보였다. 마지막으로 각도 추적에서도 전체 시나리오 구간에서 안정적인 동작을 확인하여 초고속 탄도탄 표적의 추적에 적합함을 입증하였다.

• 전기학회논문지
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• 제61권5호
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• pp.726-734
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• 2012

In this paper, a practical warhead tracking filter is proposed for developing a FMCW (Frequency Modulation Continuous Wave) seeker with anti-ballistic missile capability. For reliable warhead tracking, the measurement originated from the warhead section of a ballistic target should be separated from other measurements. Futhermore, since the FMCW seeker is based on triangular frequency modulation, the multiple measurements obtained in different chirp periods should be properly associated. As a systematic way to solve the problem, the measurement pairing problem under cluttered environment is reformulated as a data association filtering problem and the PDA (Probabilistic Data Association) scheme is applied. The proposed warhead tracking filter provides better warhead tracking performance compared to the conventional range tracking algorithm and nearest neighbor warhead tracking filter. The effectiveness and reliability of the proposed method are verified using the FMCW seeker simulator.

• 전기전자학회논문지
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• 제11권4호
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• pp.137-144
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• 2007

함포의 사격통제장치 성능은 크게 하드웨어(H/W)적인 오차와 소프트웨어(S/W)적인 오차로 구분할 수 있으며, 이중 S/W 오차에 해당하는 표적의 위치, 속도, 가속도 등을 추정하는 추적필터 오차는 탄도계산장치의 성능에 중요한 영향을 미친다. 함포의 정확한 예상탄착점 형성과 사격시 명중률 향상을 위하여 정확한 미래위치의 표적 상태정보가 필요하다. 표적 추적필터 알고리즘은 Single Singer Model, Fixed Gain 필터 알고리즘, IMM, PBIMM등이 있다. 본 논문에서는 최근 국내 함정에 적용예정인 IMM 추적필터를 설계하였다. IMM 추적필터를 위해 CV모델, Song 모델, CTR모델을 사용하여 동역학 모델을 만들었으며, 추적성능을 Monte-Carlo 시뮬레이션을 통해 해석해 보았다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.188-188
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• 2000

The most important problem in target tracking can be said to be modeling the tracking system correctly. Although the simple linear dynamic equation for this model has used until now, the satisfactory performance could not be obtained owing to uncertainties of the real systems in the case of designing the filters baged on the dynamic equations. In this paper, we propose the extended robust Kalman filter (ERKF) which can be applied to the real target tracking system with the parameter uncertainties. A nonlinear dynamic equation with parameter uncertainties is used to express the uncertain system model mathematically, and a measurement equation is represented by a nonlinear equation to show data from the radar in a Cartesian coordinate frame. To solve the robust nonlinear filtering problem, we derive the extended robust Kalman filter equation using the Krein space approach and sum quadratic constraint. We show the proposed filter has better performance than the existing extended Kalman filter (EKF) via 3-dimensional target tracking example.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권1호
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• pp.22-30
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• 2003

A Coordinate-Transformation Extended Robust Kalman Filter (CERKF) designed in the Krein space is proposed, and then applied to a nonlinear incoming ballistic missile tracking system with parameter uncertainties. First, the Extended Robust Kalman filter (ERKF) is proposed to handle the nonlinearity of measurement equation which occurs whenever the polar coordinate system is transformed into the Cartesian coordinate system. Moreover, linearization error inevitably occurs and deteriorates the tracking performance, which is considerably reduced by the proposed CERKF. Through the simulation results, we show that the proposed CERKF, which uses the measurement coordinate system, has less RMS error than the previous ERKF which is designed in the Krein space using the Cartesian system. We also verify that the robustness and the stability of the proposed filter are guaranteed in two radars: the phased way radar and the scanning radar

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.99-102
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• 2003

A new interacting multiple model (IMM) method using genetic algorithm (GA)-based intelligent input estimation(IIE) is proposed to track a maneuvering target. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown acceleration input by a fuzzy system using the relation between maneuvering filter residual and non-maneuvering one. The GA is utilized to optimize a fuzzy system fur a sub-model within a fixed range of acceleration input. Then, multiple models are composed of these fuzzy systems, which are optimized for different ranges of acceleration input. In computer simulation for an incoming ballistic missile, the tracking performance of the proposed method is compared with those of the input estimation(IE) technique and the adaptive interacting multiple model (AIMM) method.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권3호
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• pp.98-109
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• 2006

Fire control system(FCS) errors can be classified as hardware errors, filter prediction errors, effective ballistic function errors, and aiming errors. Among these errors, the filter prediction errors are the most significant error sources. To reduce them, a target future position calculation method using the acceleration estimate is suggested and it is compared with the constant velocity target prediction method. Simulation results show that the suggested method has better performance than the constant velocity prediction method. Target tracking algorithm is established with multiple target tracking filters based on IMM structure.