Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Automotive radar target tracking method of iterative square root CKF (Cubature Kalman Filtering) on the basis of noise compensation

A target tracking and automotive radar technology, applied in the field of target tracking, can solve problems such as state estimation errors

Active Publication Date: 2018-07-20
NANJING UNIV OF POSTS & TELECOMM
View PDF8 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the process of automotive radar target tracking, due to the nonlinearity of the measurement equation, the real-time irregular changes in the position and speed of the target to be measured, and the complex driving environment, the state estimation is prone to large errors. The SRCKF algorithm is There is still room for improvement in such applications

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Automotive radar target tracking method of iterative square root CKF (Cubature Kalman Filtering) on the basis of noise compensation
  • Automotive radar target tracking method of iterative square root CKF (Cubature Kalman Filtering) on the basis of noise compensation
  • Automotive radar target tracking method of iterative square root CKF (Cubature Kalman Filtering) on the basis of noise compensation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0042] figure 1 It is the invention flow chart of the present method, specifically as follows:

[0043] 1. Kinematics model and observation model of vehicle radar target tracking;

[0044] Ignoring the height factor, in the x-y two-dimensional Cartesian coordinate system, define the motion state of the target to be measured next to the car body as a 6-dimensional state vector, namely Each variable of the vector represents the target lateral distance x and lateral velocity in the vehicle body coordinate system at time k respectively , lateral acceleration , longitudinal distance y, longitudinal velocity and longitudinal acceleration , the superscript T is the transpose of the matrix or vector, the same below. ;

[0045] The target informa...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an automotive radar target tracking method of iterative square root CKF (Cubature Kalman Filtering) on the basis of noise compensation. The method comprises the following stepsthat: firstly, setting a system initial value, and calculating a cubature point value in a time update stage; spreading the cubature point; estimating a one-step prediction state and an error covariance square root factor; in a measurement update stage, importing a Gauss-Newton nonlinear iteration method to carry out iteration update, and calculating the cubature point during each-time iteration;spreading the cubature point; calculating measurement estimation; calcauting the square root factor of an innovation covariance and a cross covariance matrix; calculating Kalman gain; updating a current iteration state, and estimating the square root factor of an error covariance; judging whether an iteration termination condition is achieved or not; updating a current state, and estimating the error covariance square root; and in the measurement update process, regulating the noise compensation factor to optimize state estimation. By use of the method, accuracy and stability in an automotiveradar target tracking process can be effectively improved.

Description

technical field [0001] The invention relates to the technical field of target tracking, in particular to an automotive radar target tracking method based on noise-compensated iterative square root CKF. Background technique [0002] The essence of the target tracking process of automotive radar is a nonlinear filtering problem. The vehicle radar directly measures the radial distance, azimuth and radial velocity of the target, and realizes the estimation of the horizontal and vertical distance and velocity of the target in front of the vehicle through nonlinear conversion. This tracking process is due to the Affected by noise and nonlinearity, the filter algorithm has high requirements for fastness, robustness and filtering accuracy. The current automotive radar target tracking mostly uses Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). Non-linear filtering such as volumetric Kalman filter (CKF), these filtering algorithms have their own advantages and disadvan...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/50G01S13/72
CPCG01S13/72G06F30/20Y02T90/00
Inventor 熊星王彩玲荆晓远
Owner NANJING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com