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Adaptive fast detection method of cfar in sar image based on multi-thread

A detection method and self-adaptive technology, applied in radio wave measurement systems, radio wave reflection/re-radiation, measurement devices, etc., can solve problems such as failure to meet real-time requirements, and achieve the effect of increasing speed and detection speed

Active Publication Date: 2018-04-13
SHANDONG UNIV OF SCI & TECH
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Problems solved by technology

[0004] Gui Gao (Gao, 2009) and others improved the Salazars algorithm and proposed an AC-based CFAR adaptive fast detection algorithm. This algorithm can increase the detection speed correspondingly while ensuring the accuracy of the target, but it still cannot reach Real-time Requirements for Ship Target Detection in Military Operations

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  • Adaptive fast detection method of cfar in sar image based on multi-thread
  • Adaptive fast detection method of cfar in sar image based on multi-thread
  • Adaptive fast detection method of cfar in sar image based on multi-thread

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[0057] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0058] 1. The source of fast algorithm design ideas

[0059] The self-adaptive fast algorithm for ship detection proposed in this paper adopts some ideas in the classic CFAR algorithm. (1) The index value used in VI-CFAR (Smith and Varshney, 1997, Smith and Varshney, 2000) can select the target point in the background clutter area, but the index matrix should be obtained by adaptive threshold instead of Experience gained. (2) The CFAR algorithm based on Beta-prime distribution proposed by Salazar (Salazar, 1999) has a good detection effect in the uniform clutter and multi-background environment, so the target points in the multi-background environment should be detected locally individually to ensure The accuracy of target detection. (3) The algorithm proposed by Bisceglie (Bisceglie and Galdi, 2005, Bisceglie and Galdi, 2001) eliminates poss...

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Abstract

The invention discloses a multi-threaded SAR image CFAR self-adaptive fast detection method, which belongs to the field of ship detection system. Firstly, the histogram statistical CFAR algorithm is used to calculate the global threshold to complete the fast screening of possible target points in the image and obtain the index. matrix; then, through the index matrix, the sliding window detection based on K distribution is carried out on the screened possible target points. According to statistics, the possible ships are screened out according to the smallest ship pixel area; by analyzing the detection results of the algorithm on SAR images, it is concluded that the algorithm is more suitable for use in the ship detection system. Compared with the Salazar algorithm, the fast detection method proposed by the present invention has greatly improved the detection speed without reducing the detection accuracy, and is more suitable for application in ship detection systems.

Description

technical field [0001] The invention belongs to the field of ship detection systems, and in particular relates to a multithread-based SAR image CFAR self-adaptive fast detection method. Background technique [0002] With the development of global marine technology, the requirements for real-time and accuracy of ship detection are getting higher and higher. So far, many algorithms for target detection have been proposed in the literature. Among these algorithms, the constant false alarm rate (Constant False Alarm Rate, CFAR) detection algorithm is simple in calculation, adaptive in threshold value, and fast in complex background detection (Salazar, 1999, Bisceglie and Galdi, 2005) is considered an important algorithm for SAR image target detection, and has been widely used in many ship detection systems (Crisp, 2004). [0003] Achieving target detection using CFAR usually requires selecting an appropriate clutter distribution model and detector. The statistical models used ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S13/90
CPCG01S13/90G01S13/9027
Inventor 王瑞富李洁朱金山
Owner SHANDONG UNIV OF SCI & TECH
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