Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Adaptive CFAR Algorithm using Two-Dimensional Block Estimation

이차원 블록 추정을 이용한 적응 CFAR 알고리즘

  • Published : 2005.01.01
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Abstract

Adaptive constant false alarm rate(CFAR) algorithm is used for good detection probability as well as constant false alarm rate in clutter background. Especially, filtering technique adaptive to spatial variation is necessary for improving detection quality in non stationary clutter environment which has spatial correlation and large magnitude deviation. In this paper, we propose a two-dimensional block interpolation(TBI) adaptive CFAR algorithm that calculates the node estimate in the fred two dimensional region and subsequently determines the final estimate for each resolution cell by two-dimensional interpolation. The proposed method is efficient for filtering abnormal ejection by adopting distribution median in fixed region and also has advantage of reducing required memory space by using estimation method which gets final values after calculating the block node values. Through simulations, we show that the proposed method is superior to the traditional adaptive CFAR algorithms which are transversal or recursive in aspect of the detection performance and required memory space.

적응 CFAR(Constant False Alarm Rate) 알고리즘은 클러터 배경 환경에서 일정한 오경보 율을 유지하면서 탐지확률을 높이기 위해 사용된다. 특히 공간 상관관계, 크기 편차가 큰 비 균일한 클러터 환경에서 탐지성능을 향상시키기 위해서는 공간변화에 적응적인 필터링 기법이 요구된다. 본 논문에서는 클러터 배경추정을 위해 이차원적으로 영역을 구분하여 대표 추정 값을 구하고, 보간(interpolation) 필터를 이용하여 최종 추정 값을 결정하는 이차원 블록 보간(Two-dimensional Block Interpolation : TBI) 적응 CFAR 알고리즘을 제안한다. 제안한 방법은 부분영역의 히스토그램 분포 중앙값을 영역 추정 값으로 선택함으로 불규칙 간섭신호 제거에 효과적이며, 블록 노드 추정 값을 이용하여 각 셀에 대한 최종 추정 값을 얻는 방식을 취함으로 인해 거리 셀 수가 많고, 고도 빔 수가 많은 시스템에서 클러터 필터링에 필요한 메모리 공간을 줄이는데 이점이 있다. 컴퓨터 모의실험을 통해 기존의 트랜스버설(transversal) 방식, 회귀(recursive)방식의 적응 CFAR 알고리즘과 탐지성능, 필요메모리 측면에서 성능을 비교하여 제안한 방법의 우수성을 확인한다.

Keywords

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