Distributed target tracking method based on improved joint probability data association

A data association and target tracking technology, applied in the field of distributed filtering and target tracking, can solve the problems of reducing the calculation amount of the algorithm, unable to meet the real-time requirements of the tracking algorithm, increasing the calculation amount of the joint probability, etc., and achieve a reduced time. Effect

Active Publication Date: 2017-02-22
HARBIN ENG UNIV
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Problems solved by technology

[0003] The Joint Probability Data Association (JPDA) method is an ideal algorithm in the data association algorithm of multi-target tracking, but the number of joint events increases exponentially with the increase of the number of echoes, which leads to the loss of joint probability. The amount of calculation is greatly increased, which cannot meet the real-time requirements of the tracking algorithm, so reducing the amount of calculation of the algorithm is one of the main improvement directions of JPDA

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  • Distributed target tracking method based on improved joint probability data association
  • Distributed target tracking method based on improved joint probability data association
  • Distributed target tracking method based on improved joint probability data association

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Experimental program
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Embodiment

[0105] Embodiment: Based on the radar sensor, a simulation experiment is carried out on the proposed distributed UKF-IJPDA algorithm to verify the performance of the algorithm.

[0106] The hypothetical conditions are as follows: there are 3 targets and 10 sensor nodes, each sensor can obtain the position information of 3 targets, and each target moves in a straight line at a nearly constant speed. Take the position and velocity in the direction of the corresponding coordinate axis of the two-dimensional rectangular coordinate system of the plane as the state of the target, establish a state CV model, and use the radial distance and azimuth of the radar sensor as observation values ​​to establish a sensor model. The obtained tracking model is as follows: Formula (22) shows:

[0107]

[0108]

[0109] where (b x ,b y ) is the position of the sensor, each sensor works independently, and it is assumed that the noise variance characteristics of all sensors are consistent, R=...

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Abstract

The invention belongs to the technical field of distributed filtering and target tracking, and particularly relates to a distributed target tracking method based on improved joint probability data association. The method provided by the invention comprises the steps that (1) a motion model is established for each target of a sensor multi-target tracking system; (2) a data association filtering method is carried out on each sensor to acquire the state estimation of the target within a detection range related to each sensor; and (3) spatial association is carried out on the state estimation of each sensor, and then the state estimation of the same target is fused to acquire the final target state estimation value. The simulation result proves the performance of the algorithm. The method can achieve the same precision as a traditional joint improved version data association method, and is superior to a joint probability data association method in time performance. The time of the algorithm is reduced.

Description

technical field [0001] The invention belongs to the technical field of distributed filtering and target tracking, and in particular relates to a distributed target tracking method based on improved joint probability data association. Background technique [0002] The surrounding environment problems considered in the research of single target tracking method are relatively simple. From the research of single target single sensor measurement information to the research of single target multi-sensor information, more and more comprehensive measurement information is integrated for target tracking, in order to obtain high precision target state information. Due to the complexity and variability of the modern external environment, the research on target tracking has gradually developed from single target tracking in simple environments to tracking modes in complex environments and multi-target environments. At this time, the tracked target information measured by the sensor may...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41
CPCG01S7/41
Inventor 李宁张勇刚张滋蒋敏
Owner HARBIN ENG UNIV
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