BVI-CFAR target detection algorithm of variation index based on Bayesian interference control
A BVI-CFAR, target detection algorithm technology, applied in the direction based on specific mathematical models, calculations, calculation models, etc., can solve the problem of detection probability decline and other issues
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[0020] figure 1 A BVI-CFAR object detection algorithm based on variation index of Bayesian interference control is demonstrated, which includes the following steps:
[0021] Step 1, compared with the traditional variation index detector (VI-CFAR), such as figure 2 shown. This paper adopts a more refined segmentation method, divides the sliding window into four parts, and then calculates its second-order statistics V for each part VI and statistical sums, such as image 3 shown. Step 2, will get the second order statistics V VIA ,V VIB ,V VIC ,V VID and the statistical threshold K VI For comparison, the mean ratio MR0, MR1, MR2 and the mean threshold K MR comparing.
[0022] Choose the threshold K BVI =5, the probability that the detector exceeds this value in a uniform environment is less than 1%, so K can be selected BVI =5 is the threshold of the second statistic of the VI-CFAR detector, and the threshold of the BVI-CFAR detector is less affected by interference...
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