• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.9
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• pp.828-836
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• 2015

In this paper, the assessment technique for track accuracy in the phased array radar is proposed. It is assumed that ${\alpha}-{\beta}$ tracking filter to track the target is established in the phased array radar. In order to assess the track accuracy strictly, we should use the real target position data acquired from the special instrument, ACMI(Air Combat Maneuvering Instrument) pod or DGPS(Differential Global Positioning System). However, this method leads to increase the experiment cost and test time. We derive the relationship between the residuals of tracking filter and the standard deviations of range and angle tracking errors which are assigned as track assessment index. The theory of sample variance is introduced in this assessment because track accuracy has to be calculated with many residual samples.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.474-477
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• 1989

The PDA (Probabilistic Data Association) Filter proposes a new approach to the problem of tracking when the source of the measurement data is uncertain. The PDA filter shows good simulation results in a known clutter density. In this paper the PDA filter has been modified so that it can be applied when the clutter density is not known.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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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

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.121-130
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• 2000

A practical method is proposed to improve hit probability of the digital gun fire control system, when the measured rate of the tracking sensor becomes biased under some operational situation. For ground moving target it is shown that the well-known Kalman filter which uses position measurement only can be optimally used to eliminate the rate bias error. On the other hand, for 3D moving aircraft we present a new algorithm which incorporate FIR-type filter, which uses position and rate measurement at the same time, and the fixed-lag smoother using position measurement only, and show that it has the optimal performance in terms of both estimation accuracy and response time.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.255-263
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• 2012

This paper presents the smart interacting multiple model (SIMM) using the concept of predicted point and maximum noise level. Maximum noise level means the largest value of the mere noises. We utilize the positional difference between measured point and predicted point as acceleration. Comparing this acceleration with the maximum noise level, we extract the acceleration to recognize the characteristics of the target. To estimate the acceleration, we propose an optional algorithm utilizing the proposed method and the Kalman filter (KF) selectively. Also, for increasing the effect of estimation, the weight given at each sub-filter of the interacting multiple model (IMM) structure is varying according to the rate of noise scale. All the procedures of the proposed algorithm can be implemented by an on-line system. Finally, an example is provided to show the effectiveness of the proposed algorithm.

• Journal of Advanced Navigation Technology
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• v.4 no.1
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• pp.50-66
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• 2000

For a long time target maneuvers in tracking problem have been a difficult task to handle. Once a maneuvering such as abrupt change in target accelerations occur, the tracking fiter no longer yields a reasonable estimate of the target position. In order to resolve this cumbersome maneuvering problem. Advanced methods have here proposed : Colored noise, IE(Input Estimation), VD(Variable Dimension), IMM(Interaction Multiple Model), Jump-type processes and jerk model, etc. In this paper, tracking performance of the jerk model is analyzed. Jerk model in which the derivative of target acceleration is included as a state recently attracted considerable attraction. Firstly 3-dimensional Kalman filter is described on the basis of jerk model. Then using this filter, Monte-Carlo simulations are carried out and the filter formance with respect to the variation of jerk time-constant is analyzed. Especially, since jerk model's transient performance is expected to be poor, the performance of analysis of transient response of the model is included too.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.882-889
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• 2014

This paper deals with a filterbank based on the IMM (Interacting Multiple Model) that combines data from a sensor and uses them selectively depending on a level of maneuver. Furthermore, within the maneuver interval, the existing IMM filter has disadvantages such as unnecessary target estimation errors caused by using a constant velocity model and an increase of computation load because of a fixed structure. On the other hand, the proposed IMM filterbank overcomes these disadvantages by using three model groups and designs a filterbank to cope with a wideband-maneuvering target. The performances of the IMM filterbank was evaluated through comparison with the existing IMM via computer simulations. The results show good performances for a wideband-maneuvering target.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.303-306
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKF uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1961-1963
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• 2001

In a target tracking problem, the radar glint noise has non-Gaussian heavy-tailed distribution and will seriously affect the target tracking performance. In this study, an extended robust $H_{\infty}$ was developed which can significantly improve the tracking performance when glint noise is present. Through the computer simulations, the proposed filter showed superior and robust tracking performance compared with other extended Kalman filters.