Multi-hypothesis tracking method based on infrared target gray-scale cross-correlation and angle information

An infrared target and cross-correlation technology, which is applied in the field of multi-hypothesis tracking based on infrared target grayscale cross-correlation and angle information, can solve the problems of easily lost targets, poor real-time performance, and small amount of calculation, and achieve fast confirmation and fast deletion. , the effect of reducing the number of assumptions

Active Publication Date: 2018-05-08
LUOYANG INST OF ELECTRO OPTICAL EQUIP OF AVIC
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Problems solved by technology

The global nearest neighbor method and the joint probability data interconnection method have a small amount of calculation and high real-time performance, but they are easy to lose targets in a dense clutter environment; the multi-hypothesis tracking algorithm is the most accurate method for solving multi-target data association in a high clutter environment method, but the algorithm has a large amount of calculation and poor real-time performance

Method used

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  • Multi-hypothesis tracking method based on infrared target gray-scale cross-correlation and angle information
  • Multi-hypothesis tracking method based on infrared target gray-scale cross-correlation and angle information
  • Multi-hypothesis tracking method based on infrared target gray-scale cross-correlation and angle information

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Embodiment Construction

[0036] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0037] The experimental data source of the embodiment includes a 200-frame image sequence (640*512) and corresponding detected target position data.

[0038] The specific implementation steps of the present invention are as follows:

[0039] 1) Data association

[0040] The data association adopts the predicted track, which has been filtered for k times. Calculate the residual error of the filter according to the Kalman filter principle Residual covariance matrix S and residual norm d 2 :

[0041]

[0042] S=HP(k / k)H T +R(k) (2)

[0043]

[0044] In the formula, H is the measurement matrix, is the filter output, P(k / k) is the error covariance matrix, R(k) is the measurement noise covariance matrix, c is the correlation threshold, and the adaptive threshold is adopted.

[0045] 2) Track evaluation

[0046] First, take the track Track(k-1) in the 5...

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Abstract

The invention relates to a multi-hypothesis tracking method based on infrared target gray-scale cross-correlation and angle information. Infrared target gray-scale cross-correlation characteristic information and angle information are used, a track confidence evaluation model in the multi-hypothesis tracking method is reconstructed, the track confidence evaluation model based on the gray-scale cross-correlation and angle information is established, the model is used to complete confidence calculation, the rapid confirmation and rapid deletion of multiple target tracks are achieved, the numberof follow-up track hypotheses is reduced, a track creation time is effectively improved, and the algorithm complexity is reduced. Therefore, the track confidence evaluation model based on the infraredtarget gray-scale cross-correlation and angle information can achieve a better effect, and the method of the invention is better than a multi-hypothesis tracking method using an angle information track evaluation model.

Description

technical field [0001] The invention belongs to the technical field of data processing, and relates to a method for multi-target tracking, in particular to a multi-hypothesis tracking method based on infrared target gray level cross-correlation and angle information. Background technique [0002] Due to the small amount of information that can be obtained by the infrared warning system, generally only the target angle information, and there are a lot of false alarms and clutter in the obtained target information, there is a contradiction between real-time and accuracy in multi-target tracking, and it needs to be further studied . At present, multi-target tracking algorithms can be summed up mainly including Global Nearest Neighbor (GNN), Joint Probabilistic Data Association (JPDA) and Multiple Hypothesis Tracking (MHT). The global nearest neighbor method and the joint probability data interconnection method have a small amount of calculation and high real-time performance, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/277G06T7/246
CPCG06T2207/10016G06T2207/10048G06T2207/30241G06T7/246G06T7/277
Inventor 夏庆施明绚赵凯生
Owner LUOYANG INST OF ELECTRO OPTICAL EQUIP OF AVIC
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