Weak target detection and tracking method based on box particle probability hypothesis density filter

A technique of probabilistic hypothesis density and weak target detection, which is applied in image data processing, instruments, calculations, etc., can solve the problems of high computational complexity and low operating efficiency, and achieve improved computational efficiency, accurate target state, and reduced computational complexity Effect

Active Publication Date: 2018-02-23
GUILIN UNIV OF ELECTRONIC TECH
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Problems solved by technology

[0003] The present invention aims to solve the problems of high computational complexity and low operating efficiency in the existing PHD filtering pre-detection tracking method, and provides a weak target detection and tracking method based on box particle probability assumption density filtering

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  • Weak target detection and tracking method based on box particle probability hypothesis density filter
  • Weak target detection and tracking method based on box particle probability hypothesis density filter
  • Weak target detection and tracking method based on box particle probability hypothesis density filter

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Embodiment Construction

[0025] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific examples and with reference to the accompanying drawings.

[0026] Aiming at the problems of high computational complexity and low computational efficiency in the pre-detection tracking algorithm of the existing particle probability assumption density filter, the invention studies the weak target detection and tracking method.

[0027] (1) Establish the state equation of the target and the observation intensity measurement equation (that is, the sensor observation equation).

[0028] (1.1) Establish the state equation of the target:

[0029]

[0030] in, is the state of the target at time k, and represent the position, velocity and strength of the target, respectively. v k is the known process noise, f k (.) is a known nonlinear function, N k is the number of targets at ...

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Abstract

The invention discloses a weak target detection and tracking method based on box particle probability hypothesis density filter; the method comprises the following steps: using a box particle PHD filter method to process a weak target under low signal to noise ratio conditions, using mean value filtering to weaken single point edge noises so as to highlight a target located area, and taking the target located area as section measurement according to the maximum uncrossed principle; using dozens of box particles to replace several hundreds of point particles, thus effectively reducing the calculating complexity, improving the calculating efficiency, and obtaining a more accurate target state in the same time.

Description

technical field [0001] The invention relates to the technical field of target detection and tracking, in particular to a weak target detection and tracking method based on box particle probability hypothesis density filtering. Background technique [0002] Track-before-detection (TBD) is an effective method to solve the problem of Small Targets Detection and Tracking (SDT) under low SNR conditions. TBD technology usually does not need to set the threshold in advance, but directly uses the original measurement data to complete the detection and tracking of the target, so that the information of the target can be preserved to the maximum extent, thus showing better detection and tracking performance than traditional methods. Probabilistic Hypothesis Density (PHD) filtering is a filtering based on stochastic finite set theory. PHD can effectively avoid data association problems and solve measurement uncertainty problems. Therefore, some scholars have applied PHD filtering to t...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/246G06T7/277
CPCG06T7/246G06T7/277G06T2207/10016G06T2207/20024G06T2207/20076
Inventor 吴孙勇宁巧娇薛秋条蔡如华刘义强孙希延纪元法
Owner GUILIN UNIV OF ELECTRONIC TECH
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