Self-adaptive non-trace kalman filtering method of GPS and BDS dual-mode satellite navigation system

An unscented Kalman, navigation system technology, applied in the filtering field of satellite navigation system, can solve the problems of difficult calculation, linear error, reduce model accuracy, etc., to avoid deception interference, reduce error rate, and reduce switching frequency.

Active Publication Date: 2019-09-13
深圳市联和安业科技有限公司
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Problems solved by technology

[0003] In the prior art, please refer to the Chinese invention patent application document with the application number 201710724015.6, the publication number 109425876A, and the name "an improved Kalman filter method for improving positioning accuracy". The defect of this technical solution is

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  • Self-adaptive non-trace kalman filtering method of GPS and BDS dual-mode satellite navigation system
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  • Self-adaptive non-trace kalman filtering method of GPS and BDS dual-mode satellite navigation system

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[0055] The present invention will be described in more detail below in conjunction with the drawings and embodiments.

[0056] The invention discloses an adaptive untracked Kalman filtering method for GPS and BDS dual-mode satellite navigation systems, please refer to figure 1 , The method includes:

[0057] Step S1, establish a nonlinear system model. Set the model of the nonlinear system as:

[0058]

[0059] Where x k Is the state vector at time k, z k Is the observation vector at time k, f k (·) and h k (·) are the state function and observation function of the nonlinear system, w k And v k It is Gaussian white noise that is not correlated with each other, and the mean and covariance matrix of the two satisfy:

[0060]

[0061] In the formula, q is the average value of state noise, r is the average value of observed noise;

[0062] Since land vehicles can be roughly regarded as a two-dimensional plane of motion carrier, the motion on the two-dimensional plane can be decomposed int...

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Abstract

The invention discloses a self-adaptive non-trace kalman filtering method of a GPS and BDS dual-mode satellite navigation system. The method comprises the steps of 1, performing non-linear system modeling; 2, performing newton motion law scattering, and performing equivalent substitution to meet a model of a non-linear system; and 3, selecting a GNSS working system with relatively optimal horizontal precision by an HDOP self-adaptive optimal selection algorithm to provide GNSS data, substituting the data into the equivalent substitution model of the non-linear system, processing a mean value and non-linear transfer of covariance by a non-trace transformation method, performing Sigma point sampling by a UKF algorithm to solve the uncertainty of noise, estimating and modifying the noise in real time to solve the non-linear characteristic of an integrated navigation system, and deducing a noise statistic estimator to perform real-time estimation and modification on unknown or inaccurate noise statistic based on a maximum likelihood criterion. The method can obviously improve the precision of the GPS and BDS dual-mode satellite navigation system, and has good effects on processing system model non-linearity and noise statistic characteristic uncertainty.

Description

Technical field [0001] The invention relates to a filtering method of a satellite navigation system, in particular to an adaptive unscented Kalman filtering method of a GPS and BDS dual-mode satellite navigation system. Background technique [0002] With the development of society, the increase of vehicles and the increasingly complicated urban traffic conditions, people have put forward higher requirements for the accuracy of positioning and navigation instruments. But so far, all existing systems for positioning and navigation instruments have certain limitations, making these instruments unable to fully meet people's needs. In order to improve urban traffic and meet people's needs, to achieve high-precision, all-weather, and global positioning, a variety of positioning and navigation systems can be combined to maximize strengths and avoid weaknesses to form a multiple organic integrated navigation system, thereby improving the accuracy and reliability of the positioning naviga...

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Application Information

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IPC IPC(8): G01S19/24
CPCG01S19/24
Inventor 罗楚江王洽和陈靖王铠帆谢达裕王景森徐虎白明雷杰曾清林许祖浩陈志朋黄钰平
Owner 深圳市联和安业科技有限公司
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