Two-Dimensional Radar Target Tracking Using a Double-Gate Converted Measurement Kalman Filter

doi:10.22716/sckt.2026.14.1.003

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2026 Vol.14, Issue 1 Preview Page Next Page

Research Article

Two-Dimensional Radar Target Tracking Using a Double-Gate Converted Measurement Kalman Filter 더블 게이트 CMKF를 이용한 2차원 레이더의 객체 추적: Dong-Gyu Lee¹
이동규¹; ¹Professor, Dept. of Software Convergence, Shinhan University

¹신한대학교 소프트웨어융합학과 교수

31 March 2026. pp. 23-32

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Abstract

본 연구는 2차원 레이더에서 발생하는 극좌표 측정의 비선형성 및 잡음으로 인해 추적 성능이 저하되는 문제를 해결하기 위해 Converted Measurement Kalman Filter(CMKF) 기반의 상태추정 기법을 적용하였다. CMKF는 거리–방위각 측정치를 직교좌표로 변환할 때 발생하는 바이어스와 분산 왜곡을 보정하여 보다 안정적인 추정값을 제공한다. 또한 본 연구에서는 등속 구간에서는 작은 게이트로 오탐을 줄이고, 기동 구간에서는 확장된 게이트로 연관 실패를 방지하는 더블 게이트(Double Gate) 구조를 제안하였다. 다양한 기동 시나리오(정속, 선회, 급가속)를 포함한 시뮬레이션 결과, 제안된 기법은 연관률, 트랙 유지율, 예측 오차 측면에서 일관된 성능을 보였다. 따라서 제안된 더블 게이트 기반 CMKF는 고기동 환경에서 안정적인 레이더 표적 추적을 제공하는 효과적인 방법임을 확인하였다.

This study applies a Converted Measurement Kalman Filter (CMKF)–based state estimation method to address performance degradation caused by the nonlinearity and noise inherent in polar-coordinate measurements of 2D radar systems. CMKF compensates for bias and covariance distortion introduced during the conversion of range–azimuth measurements into Cartesian coordinates, providing more stable state estimates. In addition, a Double-Gate structure is proposed, in which a small gate is used during constant-velocity intervals to reduce false associations, while an expanded gate is applied during maneuvering intervals to prevent association failures. Simulation experiments covering various motion scenarios—including straight motion, turning, and rapid acceleration—demonstrate that the proposed method achieves consistent performance in terms of association rate, track continuity, and prediction error. These results confirm that the CMKF with the proposed Double-Gate strategy is an effective approach for stable radar target tracking in highly maneuvering environments.

Keywords

Converted Measurement Kalman Filter

Radar Target Tracking

Double Gate

Maneuvering Target Tracking

References

정보영, 황익호, 나원상, “레이더 극좌표계 측정치를 활용한 점근 불편향 선형 표적추적 필터”, 제어·로봇·시스템학회논문지,제30권 제3호, pp. 267-275, 2024.
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최인오, 강기봉, 김시호, 정주호, 김경태, 박상홍, “기동특성을 사용한 우주표적들 간의 변별 성능 분석”, 한국정보기술학회논문지, 제15권 제11호, pp. 55-63, 2017.
10.14801/jkiit.2017.15.11.55
X. Qin, X. Feng, J. Jiang, and W. Wu, “A sequential converted measurement kalman filter with doppler measurements in ECEF coordinate system”, Chinese Journal of Electronics, Vol. 25, No. 1, pp. 139-145, 2016.
10.1049/cje.2016.01.021
S. Wang, and Q. Bao, “Decorrelated unbiased converted measurement for bistatic radar tracking”, Journal of Micro/Nanopatterning, Materials, and Metrology, Vol.15, No. 1, pp. 1650, 2021.
10.1117/1.JRS.15.016507
S. Li, D. Zhou, Y. Li, R. Du, and J. Liu, “A stability guaranteed variational bayesian converted measurement kalman filter for radar tracking with unknown noise covariances”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 61, No. 2, pp. 3763-3781, 2024.
10.1109/TAES.2024.3488679
김성원, 권택익, 조현덕, “고밀도 클러터 환경에서 비선형 표적추적에 강인한 자료결합 게이트 기법”, 한국음향학회지, 제40권 제2호, pp. 109-120, 2021.
유태훈, 방현태, 윤원근, “해상 레이더 데이터를 이용한 IMM-PDAF 기반 다중 객체 추적”, 제28권 제5호, pp. 640-649, 2024.
U. Niesen, and J. Unnikrishnanm “Joint beamforming and association design for MIMO radar”, IEEE Transactions on Signal Processing, Vol. 67, No. 14, 2019.
10.1109/TSP.2019.2918998
K. Jaro´s, and W. Buda “Analysis of association gates in radar tracking based on Kalman filter”, Proc. of SPIE, Vol. 11442, 1144206, 2020.
10.1117/12.2565276
B.-S. Yaakov, “Kalman filtering techniques for radar tracking”, Automatica, Vol. 37, No. 6, pp. 957-958, 2001.
10.1016/S0005-1098(01)00040-1
S. Bordonaro, P. Willett, and Y. Bar-Shalom “Decorrelated unbiased converted measurement Kalman filter”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 50, No. 2, pp. 1431-1444, 2021.
10.1109/TAES.2014.120563
J. Wang, K. Zhao, S. Wei, and Z. Wei “Improved converted measurement Kalman filter for satellite-borne multi-target tracking”, The Journal of Engineering, Vol. 2019, No. 19, pp. 5880-5884, 2019.
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10.1109/TAES.2017.2760798

Information

Publisher :The Society of Convergence Knowledge
Publisher(Ko) :융복합지식학회
Journal Title :The Society of Convergence Knowledge Transactions
Journal Title(Ko) :융복합지식학회논문지
Volume : 14
No :1
Pages :23-32
DOI :https://doi.org/10.22716/sckt.2026.14.1.003

[1] 정보영, 황익호, 나원상, “레이더 극좌표계 측정치를 활용한 점근 불편향 선형 표적추적 필터”, 제어·로봇·시스템학회논문지,제30권 제3호, pp. 267-275, 2024.
10.5302/J.ICROS.2024.23.0128

[2] 최인오, 강기봉, 김시호, 정주호, 김경태, 박상홍, “기동특성을 사용한 우주표적들 간의 변별 성능 분석”, 한국정보기술학회논문지, 제15권 제11호, pp. 55-63, 2017.
10.14801/jkiit.2017.15.11.55

[3] X. Qin, X. Feng, J. Jiang, and W. Wu, “A sequential converted measurement kalman filter with doppler measurements in ECEF coordinate system”, Chinese Journal of Electronics, Vol. 25, No. 1, pp. 139-145, 2016.
10.1049/cje.2016.01.021

[4] S. Wang, and Q. Bao, “Decorrelated unbiased converted measurement for bistatic radar tracking”, Journal of Micro/Nanopatterning, Materials, and Metrology, Vol.15, No. 1, pp. 1650, 2021.
10.1117/1.JRS.15.016507

[5] S. Li, D. Zhou, Y. Li, R. Du, and J. Liu, “A stability guaranteed variational bayesian converted measurement kalman filter for radar tracking with unknown noise covariances”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 61, No. 2, pp. 3763-3781, 2024.
10.1109/TAES.2024.3488679

[6] 김성원, 권택익, 조현덕, “고밀도 클러터 환경에서 비선형 표적추적에 강인한 자료결합 게이트 기법”, 한국음향학회지, 제40권 제2호, pp. 109-120, 2021.

[7] 유태훈, 방현태, 윤원근, “해상 레이더 데이터를 이용한 IMM-PDAF 기반 다중 객체 추적”, 제28권 제5호, pp. 640-649, 2024.

[8] U. Niesen, and J. Unnikrishnanm “Joint beamforming and association design for MIMO radar”, IEEE Transactions on Signal Processing, Vol. 67, No. 14, 2019.
10.1109/TSP.2019.2918998

[9] K. Jaro´s, and W. Buda “Analysis of association gates in radar tracking based on Kalman filter”, Proc. of SPIE, Vol. 11442, 1144206, 2020.
10.1117/12.2565276

[10] B.-S. Yaakov, “Kalman filtering techniques for radar tracking”, Automatica, Vol. 37, No. 6, pp. 957-958, 2001.
10.1016/S0005-1098(01)00040-1

[11] S. Bordonaro, P. Willett, and Y. Bar-Shalom “Decorrelated unbiased converted measurement Kalman filter”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 50, No. 2, pp. 1431-1444, 2021.
10.1109/TAES.2014.120563

[12] J. Wang, K. Zhao, S. Wei, and Z. Wei “Improved converted measurement Kalman filter for satellite-borne multi-target tracking”, The Journal of Engineering, Vol. 2019, No. 19, pp. 5880-5884, 2019.
10.1049/joe.2019.0207

[13] Z. Guo, R. Xu, T. Kirubarajan, “Statically fused converted measurement kalman filters for phased-array radars”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 54, No. 2, pp. 554-568, 2018.
10.1109/TAES.2017.2760798

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