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Gain compensation self-adaptive filtering-based SINS (strap-down inertial navigation)/DVL (Doppler velocity log) combined positioning method

A technology of adaptive filtering and gain compensation, which is applied in the direction of sound wave reradiation, radio wave measurement system, navigation through speed/acceleration measurement, etc., and can solve the problem of low positioning accuracy

Active Publication Date: 2019-08-20
HARBIN INST OF TECH AT WEIHAI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the problem of low positioning accuracy due to the time-varying characteristics of the system noise of the SINS / DVL combined positioning method in complex underwater environments, and propose a SINS / DVL combined positioning method with gain compensation adaptive filtering

Method used

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  • Gain compensation self-adaptive filtering-based SINS (strap-down inertial navigation)/DVL (Doppler velocity log) combined positioning method
  • Gain compensation self-adaptive filtering-based SINS (strap-down inertial navigation)/DVL (Doppler velocity log) combined positioning method
  • Gain compensation self-adaptive filtering-based SINS (strap-down inertial navigation)/DVL (Doppler velocity log) combined positioning method

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specific Embodiment approach 1

[0100] Step 1, the system establishes the SINS / DVL combined positioning error model state variable X=[δv E δv N α β γ δL δλ ε E ε N ε U δv d δΔδC] T , where δv E and δv N α, β, γ are platform misalignment angles, δL and δλ are longitude and latitude errors, ε E , ε N , ε U is the gyro drift in the east, north and sky directions, δv d is the Doppler measurement velocity offset error, δΔ is the bias angle error, and δC is the scale coefficient error;

[0101] Step 2. The system measures the three-axis (east, north, sky) acceleration information a through the three-axis angular velocity information of the gyroscope sensitive carrier in the inertial navigation component and the accelerometer E 、a N 、a H , Velocity v obtained by Doppler log d , navigation information such as drift angle Δ and attitude;

[0102] Step 3. The system converts the acceleration components a in these three directions E 、a N 、a H Putting into formula (1) and integrating respectively...

specific Embodiment approach 2

[0192] Specific embodiment 2, this embodiment is a further description of step 7 of a SINS / DVL combined positioning method for gain compensation adaptive filtering described in specific embodiment 1, which is characterized in that the criterion for judging whether the filtering is divergent, according to the filtering The relationship between the estimated error and the expected error is judged.

specific Embodiment approach 3

[0193] Specific embodiment three, this embodiment is a further description of the SINS / DVL combined positioning method for gain compensation adaptive filtering described in specific embodiment one, which is characterized in that the filter gain compensation algorithm adopted is aimed at underwater The external disturbance of the ocean current or the sudden change of the speed and course of the underwater vehicle will cause a slight delay in the estimated value of the filtering process when tracking the real state of the underwater vehicle, thus reducing the navigation accuracy and quality. Real-time tracking of system status and reduced error accumulation.

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Abstract

The invention relates to a gain compensation self-adaptive filtering-based SINS (strap-down inertial navigation) / DVL (Doppler velocity log) combined positioning method and belongs to the technical field of high-precision SINS / DVL combined positioning. The invention aims to solve the problem of low positioning precision due to the influence of the insufficient flexibility of the filtering algorithmof conventional SINS / DVL combined navigation. The method of the invention includes the following steps that: corresponding state initial values and observation values are acquired based on the sensorinformation of a strap-down inertial navigation system and a Doppler velocity log; a corresponding system equation and observation equation based on a combined navigation error model are constructed,a gain compensation self-adaptive filtering algorithm is adopted to correct errors, so that the post-correction speed and position error information of a target is obtained; and finally, the obtainederror information and the observation information of the strap-down inertial navigation system and the Doppler velocity log are fused, so that a high-precision positioning result is obtained.

Description

technical field [0001] The invention relates to high-precision underwater positioning technology Background technique [0002] In the actual underwater positioning process, due to the complex and changeable underwater environment, the system noise and measurement noise of the strapdown inertial navigation and Doppler log combined positioning (SINS / DVL) system often have statistical characteristics. Certain time variability. In order to improve the Kalman filtering algorithm reasonably, it has a certain adaptive ability to the change of noise statistical characteristics, so as to further improve the filtering accuracy and achieve high-precision positioning. The invention adopts a filtering gain compensation method to optimize the improved self-adaptive filtering algorithm, and uses the optimized filtering algorithm to restrain the error divergence of the positioning system, thereby achieving the purpose of improving the positioning accuracy. Contents of the invention [0...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/16G01S15/02G01S15/42
CPCG01C21/165G01S15/42G01S15/86
Inventor 杨一鹏闫锋刚罗清华焉晓贞彭宇彭喜元
Owner HARBIN INST OF TECH AT WEIHAI
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