Abstract
In combination with the advantages of CA-CFAR, GO-CFAR and SO-CFAR algorithm, the VI-CFAR has strong adaptability both in homogeneous and non-homogeneous environment. However, if the interfering targets are present in both the halves of the reference sliding windows, the use of the window with the smallest mean is affected by them and therefore results in a performance degradation. In order to overcome the shortcoming, an improved VI-CFAR detector based on GOS (IVI-CFAR) is proposed in this paper. We introduce the IVI-CFAR detector and make performance simulation and analysis in homogenous and non-homogenous environment. In the homogeneous environment, the IVI-CFAR detector has some CFAR loss relative to the CA-CFAR detector. In the clutter edge environment, the IVI-CFAR detector keeps the good performance of the VI-CFAR detector. In multiple interfering targets environment, the IVI-CFAR detector performs robustly, which is similar to the OS-CFAR detector. In addition, the IVI-CFAR detector shortens the sample sorting time of the OS-CFARR detector.
Highlights
In radar and sonar signal detection, in order to get a constant false alarm (CFA R) performance, the actual average power of interfering background will be estimated by the reference cells near the test cell to adaptively set the detection threshold
The CA-CFA R detector can get close to the optimal detection performance, but in the non-homogeneous environment, the detection performance of CA-CFAR seriously declines
When the interfering targets appear in both the leading and lagging sliding window, the possibility of the VICFA R detector selecting the SO-CFAR algorith m increases, this will lead to the serious deterioration of the performance of the VI-CFAR detector
Summary
In radar and sonar signal detection, in order to get a constant false alarm (CFA R) performance, the actual average power of interfering background will be estimated by the reference cells near the test cell to adaptively set the detection threshold. In order to overcome the disadvantages of the CFA R detectors, the VI-CFA R detector was proposed by Smith and Varshney [3, 4] In this detector, the data in the reference slid ing window is used to compute two statistics VI and MR. Based on these statistics, two tests are performed in order to select the algorith ms (CA-CFA R, GO-CFA R [5] and SO-CFA R [6]) to be used for the estimation of the clutter power in the test cell [7].
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