Hybrid square root cubature Kalman filtering method used for target tracking

A Kalman filter and target tracking technology, which is applied in the fields of target tracking, car assisted driving, car autonomous driving and car active safety, can solve problems such as difficult to meet the high real-time requirements of the system, achieve strong real-time performance and improve filtering efficiency Effect

Inactive Publication Date: 2017-08-04
NANJING UNIV OF SCI & TECH
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Problems solved by technology

However, the high time complexity of SRCKF is often diffi

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  • Hybrid square root cubature Kalman filtering method used for target tracking
  • Hybrid square root cubature Kalman filtering method used for target tracking
  • Hybrid square root cubature Kalman filtering method used for target tracking

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[0056] With reference to the accompanying drawings, the implementation of the hybrid square root volume Kalman filter method for target tracking according to the present invention is as follows:

[0057] Step 1: Define the target state vector at time k Where x k , Respectively represent the distance, velocity and acceleration of the target in the X direction at time k, y k , Respectively represent the distance, speed and acceleration of the target in the Y direction at time k, the symbol T represents matrix transposition; define the target measurement vector Y at time k k =[r k ,a k ,v k ] T , Where r k , A k , V k Respectively represent the radial distance, azimuth angle and radial velocity from the target to the sensor at time k. k=1,2...n,n∈Z + .

[0058] According to the target measurement vector Y at k=0 0 Initialize the target state vector X at k=0 0 , The initialization method is shown in formula (1):

[0059] X 0 =[r 0 cos(a 0 ),v 0 cos(a 0 ),0,r 0 sin(a 0 ),v 0 sin(a 0 ),...

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Abstract

The invention discloses a hybrid square root cubature Kalman filtering method used for target tracking. The method includes the steps that according to an initialized state vector, an initialized process noise covariance square root factor, an initialized measuring noise covariance square root factor and an initialized state covariance square root factor, a state vector cubature sampling point is calculated; a measuring vector cubature sampling point and a measuring vector cubature sampling point are calculated to obtain measured vectors; a Kalman gain and a posterior state covariance square root factor are calculated; a posterior state vector is calculated. On the premise that filtering precision is unchanged, the filtering efficiency is greatly improved, and the instantaneity is very high.

Description

technical field [0001] The invention belongs to the technical field of target tracking, and in particular relates to a target tracking filtering method based on a mixed square root volumetric Kalman filter, which can be widely used in the fields of assisted driving of automobiles, autonomous driving of automobiles, active safety of automobiles, and the like. Background technique [0002] Kalman Filter (KF) is a tracking filtering algorithm widely used in the field of target tracking. The role of the Kalman filter is to estimate the motion state of the target as accurately as possible by modeling the motion process of the moving target and the sensor measurement process, using indirect and noisy measurement values. The motion state includes information such as the position, velocity and acceleration of the target. The sensor measurement model contains noise, which is called measurement noise, which means that the measurement of the target contains certain inaccuracies; the t...

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Application Information

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IPC IPC(8): G06F17/15G01C21/20
CPCG01C21/20G06F17/15
Inventor 刘华军赖少发
Owner NANJING UNIV OF SCI & TECH
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