• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.157-164
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• 2005

The conventional adaptive detectors can not maintain sufficient detection performance at the presence of non-stationary clutter with unknown characteristics. This is caused by the lack of a priori information about clutter parameters changing over radar coordinates. To solve this problem, it is necessary to use clutter classifiers which have functions, such as the selection of the applied algorithm and its parameters extraction according to clutter conditions. In this paper, we describe the implementation of a clutter environment classifier for adaptive processing. In the environment classifier implemented on Visual C++, the extraction of the parameters and selection of processing algorithm for the adaptive processing unit are possible, and the result of algorithms can be verified at each stage.

• International Journal of Aeronautical and Space Sciences
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• v.6 no.1
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• pp.8-16
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• 2005

This paper describes target detection performance of millimeter wave radar that exits on non-stationary target detection schemes in the ground clutter conditions. The comparison of various CFAR process schemes such as CA(Cell-Average)-CFAR, GO(Greatest Of)/SO(Smallest Of)-CFAR, and OS(Order Statistics)-CFAR performance are applied. Using matlab software, we show the performance and loss between target detection probability and signal to noise ratio. This paper concludes the OS-CFAR process performance is better than any others and satisfies the optimal detection probability without loss of detection in the homogeneous clutter, When range bins increase.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.101-108
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• 2005

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.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.890-895
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• 2004

This paper describes constant alarm rates process of millimeter wave radar that exits on non-stationary target detection schemes in the ground clutter conditions. The comparison of various CFAR processes such as CA(Cell-Average)-CFAR, GO(Greatest Of)/SO(Smallest Of)-CFAR and OS(Order Statistics)-CFAR performance are applied. Using matlab software, we show the performance and loss between detection probability and signal to noise ratio. When rang bins increase, this results show the OS-CFAR process performance is better than any others and satisfies the optimal detection probability without loss of detection in the homogeneous clutter.