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Gauss hybrid probability hypothesis density filter-based explicit multi-target tracking method

A Gaussian mixture probability, multi-target tracking technology, applied in the field of signal processing

Active Publication Date: 2019-10-25
HOHAI UNIV
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Problems solved by technology

[0005] The multi-target tracking technology based on the GM-PHD filter has not yet solved the multi-target track management in a complex environment. For this technical problem, the purpose of the present invention is to propose a kind of explicit multi-target tracking algorithm based on the GM-PHD filter. Its core technology is to use the search matrix to shield the interference of clutter in the high prior density area of ​​the target based on the label and weight of the updated Gaussian component, and realize the same labeling of the posterior information, measurement and state estimation of each target, so as to obtain Explicit multi-object tracking without additional correlator

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  • Gauss hybrid probability hypothesis density filter-based explicit multi-target tracking method

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Embodiment

[0209] The effect of the present invention is further verified and illustrated by the following simulation.

[0210] 1. Experimental conditions:

[0211] In a two-dimensional scene [-1000 1000]m×[-1000 1000]m, the motion equation of each target is:

[0212]

[0213] where x k =[x 1,k x 2,k x 3,k x 4,k ] T ,[x 1,k x 3,k ] T is the position of the target at time k, [x 2,k x 4,k ] T is the speed of the target at time k. Δ=1s is the sampling interval, σ ω =5m / s 2 . The target can appear or disappear at any time in the scene, and the survival probability p S,k = 0.95. The strength function of the appearance of the nascent target is in,

[0214] The measurement equation of the target is

[0215]

[0216] Among them, υ x,k and υ y,k are mutually independent zero-mean Gaussian white noise, and the mean square deviations are σ x =10m, σ y = 10m. The clutter is evenly distributed in the monitoring area [-1000 1000]m×[-1000 1000]m, and the number ...

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Abstract

The invention discloses a gauss hybrid probability hypothesis density filter-based explicit multi-target tracking method. According to a core technology, matrix seeking is utilized, the interference of high prior density region cluster of a target is shielded according to a label and a weight for updating a gauss component, posterior information and measurement of each target and the same labelingof state estimation are achieved, so that explicit multi-target tracking without extra relevant program is obtained; and moreover, the real-time performance similar to a basic GM-PHD filter is maintained. The method is easily implemented in engineering, and the multi-target tracking accuracy is improved very well.

Description

technical field [0001] The invention relates to an explicit multi-target tracking method based on a Gaussian mixture probability hypothesis density filter, which belongs to the technical field of signal processing. Background technique [0002] Multi-target tracking is to estimate the number and status of targets from a series of measurements, and it is widely used in military and civilian fields, for example, radar multi-target tracking. With the continuous improvement of people's demand for radar functions, its application scenarios are becoming more and more complex. Phenomena such as signal-to-noise ratio, low-signal clutter, and dense targets seriously affect the performance of the radar, increasing the probability of false alarms and reducing the probability of target detection. These will directly affect the accuracy of target state-measurement association, thereby reducing the accuracy of state estimation. The related topics of shielding various types of interferen...

Claims

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Application Information

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IPC IPC(8): G01S13/72
CPCG01S13/726
Inventor 高乙月钱弋飞蒋德富付伟蒋康辉
Owner HOHAI UNIV
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