Self-adapting interactive multiple model mobile target tracking method

An interactive multi-model, maneuvering target tracking technology, applied in special data processing applications, measuring devices, instruments, etc., can solve the problems of unreasonable Markov transition probability matrix design, target loss, and traffic accidents And other issues

Inactive Publication Date: 2014-06-11
SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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Problems solved by technology

In fact, when the motion model of the target has a certain tendency, the traditional IMM algorithm only realizes the "synthesis" between the motion models by mediating the weighting of the posterior probability of the motion model under different observation vector conditions, and does not take into account the Marl Irrationality of Cove's Transition Probability Matrix Design
[0004] In the field of transportation, when a moving car suddenly turns, accelera...

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  • Self-adapting interactive multiple model mobile target tracking method
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  • Self-adapting interactive multiple model mobile target tracking method

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Embodiment Construction

[0100] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0101] Such as figure 1 Shown is a schematic diagram of the model estimation process of the present invention.

[0102] Step 1, establish the mixed initialization input of various models in the IMM tracking model.

[0103] 1a) The motion state equation and observation equation of the target, assuming that there are r motion models, and the state transition matrix corresponding to each motion model is Φ j (1≤j≤r), the equation can be expressed as:

[0104] X(k+1)=Φ j (k|k-1)X(k)+Г j W j (k),j=1,...,r

[0105] Z(k)=C j (k)X j (k)+V j (k)

[0106] In the formula, X(k) is the system state vector at time k, Z(k) is the system observation (measurement) vector at time k, Φ j is the state transition matrix corresponding to the jth motion model, Г j is the system control quantity corresponding to the jth motion model, W j (k) represents th...

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Abstract

The invention relates to mobile tracking of vehicle targets in the communication and transportation field. A self-adapting interactive multiple model mobile target tracking method comprises the following steps of establishing mixed initialized input. including a covariance matrix of a mixed initial condition and a mixed initial state. of each model; establishing constant velocity (CV) and constant acceleration (CA) motion models; updating: calculating covariance matrix and innovation of an error according to a Kalman filter formulation; constructing a likelihood function of a target motion module by utilizing the innovation of a Kalman filter result, and calculating a Markov state transition probability matrix; carrying out estimation output after being fused by utilizing the Markov state transition probability matrix as weight of switch among each motion model. According to the self-adapting interacting multiple model mobile target tracking method disclosed by the invention, the problem that the error is increased or the tracking is failed caused by non-matching of a filter model and a target motion model due to the motion of a target in the traditional interactive multiple model algorithm is solved; the self-adapting interacting multiple model mobile target tracking method has the advantages of low calculation complexity and good tracking effect, and can be applied to target tracking of motor vehicles in the communication and transportation field.

Description

technical field [0001] The invention belongs to the field of maneuvering target tracking, and in particular relates to an adaptive interactive multi-model maneuvering target tracking method in the field of transportation when a moving car suddenly turns, accelerates, decelerates, and the like. Background technique [0002] Target tracking is to filter the target movement data received by the detection sensor combined with different observation sets generated by various uncertain information sources, and estimate the state parameters of the moving target, such as the distance, orientation, speed, acceleration, etc. of the target. [0003] The single-model maneuvering target tracking algorithm only performs well on non-maneuvering targets. When the target maneuvers, the tracking performance of the system decreases, and even causes the target to be lost. In order to track the maneuvering target, it is necessary to establish a reasonable motion model according to the motion cha...

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Application Information

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IPC IPC(8): G06F19/00G01C23/00
Inventor 杜劲松毕欣高洁田星
Owner SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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