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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

Active Publication Date: 2021-07-30
HUBEI UNIV OF TECH
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Problems solved by technology

[0004] The present application invented the BVI-CFAR target detection algorithm based on the variance index of Bayesian interference control, which solved the problem that the detection probability drops seriously when there are targets on both sides of VI-CFAR, and at the same time improved the detection accuracy of VI-CFAR detectors. The detection performance in a uniform environment provides a new method for CFAR detection

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  • BVI-CFAR target detection algorithm of variation index based on Bayesian interference control
  • BVI-CFAR target detection algorithm of variation index based on Bayesian interference control
  • BVI-CFAR target detection algorithm of variation index based on Bayesian interference control

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Embodiment Construction

[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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Abstract

The invention discloses a BVI-CFAR target detection algorithm of a variation index based on Bayesian interference control, and the algorithm comprises the steps: firstly dividing a sliding window into a front detection window and a rear detection window, then dividing the front detection window and the rear detection window into two parts, obtaining four detection windows, then employing the variation index to carry out the analysis of the process of the four sliding windows, judging the position of a window where interference possibly exists, then adopting a Bayesian sliding window interference control method, predicting and compensating window interference, and deducing an expression of the detection process of a Bayesian variation index algorithm. According to the invention, the Bayesian sliding window interference control method is applied to the variation index detection process for the first time, a good multi-target detection effect is achieved, compared with a traditional VI-CFAR algorithm, the invention has the advantages that the problem that the detection probability is greatly reduced when targets appear on the two sides of a VI-CFAR detector is solved, and by means of the application of Bayesian interference control, the influence of interference on the detection process is reduced, the detection performance of the radar in a complex environment and a multi-target environment is improved, and a new method is provided for the CFAR algorithm.

Description

technical field [0001] The invention relates to the field of radar multi-target detection and anti-interference technology, in particular to a BVI-CFAR target detection algorithm based on variation index of Bayesian interference control. Background technique [0002] With the development of society and technology, the rapid development of artificial intelligence and the automobile industry, there is no doubt that the driver's cooperation with the assisted driving system is the main form of future car travel, and the vehicle-mounted millimeter-wave radar is an important component of the assisted driving system. high research value. However, during the detection process of the radar, the received signal is not only the target signal, but also contains some real-time changing clutter signals. Faced with this situation, the radar constant false alarm rate (Constant False Alarm Rate, CFAR) processing should also be used. And born. The advent of CFAR processing technology can ke...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41G06N7/00
CPCG01S7/41G01S7/414G06N7/01Y02A90/10
Inventor 巩朋成朱鑫潮李婕王兆彬邓薇周顺贺章擎
Owner HUBEI UNIV OF TECH
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