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Fixed multi-platform passive target combined detection method

A detection method and multi-platform technology, applied in seismology, image data processing, instruments, etc. for areas covered by water, can solve problems such as inability to improve signal-to-noise ratio, and achieve the effect of ensuring detectability

Active Publication Date: 2020-10-16
HARBIN ENG UNIV
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  • Claims
  • Application Information

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Problems solved by technology

However, this method is aimed at the situation where the target is still. When the target moves slowly, the multi-frame cumulative average cannot improve the signal-to-noise ratio, but will cause false alarms.

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  • Fixed multi-platform passive target combined detection method
  • Fixed multi-platform passive target combined detection method
  • Fixed multi-platform passive target combined detection method

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Embodiment Construction

[0032] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0033] Combined graph

[0034] The invention is a fixed multi-platform passive target joint detection method, including five parts: a clustering threshold detection model, a connected area secondary discrimination model, a connected area marking model, a coordinate library generation model, and an inter-frame association model:

[0035] Clustering threshold detection model:

[0036] Step 1: Obtain a frame of position energy map based on the joint observation of passive targets on multiple platforms;

[0037] In step 1, take a frame position energy map obtained by joint long-term observation of multi-platform passive targets to ensure that it can detect weak targets. The image has p×q points, which are defined as the nth frame image, n=1,2, ..., N.

[0038] The position energy map is obtained by joint observation of passive targets ...

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Abstract

The invention provides a fixed multi-platform passive target joint detection method, which is a fixed multi-platform passive target joint detection method and comprises five parts, namely a clusteringthreshold detection model, a connected region secondary discrimination model, a connected region marking model, a coordinate library generation model and an inter-frame association model. According to the method, a position energy diagram obtained by combined long-time observation of fixed multi-platform passive targets is used as a basis; partial random noise points are filtered through threshold detection and secondary discrimination, the detectability of a weak target is ensured, then inter-frame association is performed on multiple frames of images, geometric center coordinates of a connected region are used as inter-frame association content, random false alarm points and noise are filtered to a great extent, and the motion trail of a slow motion target is reserved.

Description

technical field [0001] The invention relates to an underwater acoustic detection method, and specifically relates to a fixed multi-platform passive target joint detection method. The invention can be applied to underwater multi-platform passive target detection, and belongs to the field of underwater acoustics and underwater acoustic signal processing. Background technique [0002] With the development of information technology and people's increasing emphasis on the ocean, underwater acoustic technology has become a research hotspot in various countries, and underwater acoustic signal processing technology has also received more and more attention. Underwater passive target observation is a core content in the field of underwater acoustic signal processing. In the process of passive target observation, there is no need to actively transmit detection signals, but the receiving platform passively collects information such as target energy and azimuth angle, so as to perform ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/33G06T7/73G06T7/187G06T5/00G01V1/38
CPCG06T7/33G06T7/73G06T7/187G01V1/38G06T2207/10016G06T2207/30204G06T2207/30241G06T5/70Y02D30/70
Inventor 生雪莉刘婷杨超然殷敬伟郭龙祥
Owner HARBIN ENG UNIV
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