Heading Measurement Based on Ultrasonic and Magnetic Compass

2013 ◽  
Vol 341-342 ◽  
pp. 896-900
Author(s):  
Bao Jiang Sun ◽  
Yue Xu

Describes briefly ultrasonic positioning system (UPS) and digital magnetic compass (DMC) heading measurement principle,analyzed the advantages and disadvantages of each option. To improve the accuracy of the heading measurement, As the theoretical basis of adaptive Kalman filter, designed a kind of ups and dmc integrated navigation system. Based on both real measurement data, made a simulation experiment and confirmed the feasibility of the navigation system.

2014 ◽  
Vol 654 ◽  
pp. 181-186 ◽  
Author(s):  
Wei Lin Yuan ◽  
Yan Ma ◽  
Hua Bo Sun

The integrated positioning system increases the visible number of single satellite navigation system and improve the DOP value of single satellite navigation system. In accordance with the construction plan, BeiDou Navigation Satellite System (BDS) has started providing continuous passive positioning, navigation and timing service in the most parts of the Asia-Pacific In this paper, DOP value of GPS, BDS and the integrated navigation system are analyzed theoretically. The improvement of DOP value of GPS which resulted from present-running BDS navigation satellites is calculated by GPS/BDS observational data. The conclusions that GPS/BDS integrated navigation system will be able to improve the positioning accuracy and have useful references for the navigation and positioning application are also obtained.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Ruixin Liu ◽  
Fucheng Liu ◽  
Chunning Liu ◽  
Pengchao Zhang

This paper presents a modified Sage-Husa adaptive Kalman filter-based SINS/DVL integrated navigation system for the autonomous underwater vehicle (AUV), where DVL is employed to correct the navigation errors of SINS that accumulate over time. When negative definite items are large enough, different from the positive definiteness of noise matrices which cannot be guaranteed for the conventional Sage-Husa adaptive Kalman filter, the proposed modified Sage-Husa adaptive Kalman filter deletes the negative definite items of adaptive update laws of the noise matrix to ensure the convergence of the Sage-Husa adaptive Kalman filter. In other words, this method sacrifices some filtering precision to ensure the stability of the filter. The simulation tests are implemented to verify that expected navigation accuracy for AUV can be obtained using the proposed modified Sage-Husa adaptive Kalman filter.


2013 ◽  
Vol 760-762 ◽  
pp. 457-461
Author(s):  
Lu Zhang ◽  
Gong Liu Yang

According to high accuracy demand in the measurement field, this paper designs a high precision inertial measurement system by using DSP and ARM processor to realize carrier-phase differential GPS/INS integrated navigation. This paper chooses Kalman filter to estimate the systematic error, uses closed loop method to correct, and carries out carrier-phase differential GPS/INS data fusion. Through manipulating actual measurement data, the integrated navigation results indicate that position accuracy reaches cm level; velocity accuracy reaches cm/s level and attitude achieves high precision. The experiment proves the feasibility and effectiveness of carrier-phase differential GPS/INS integrated navigation system.


2016 ◽  
Vol 70 (3) ◽  
pp. 628-647 ◽  
Author(s):  
Narjes Davari ◽  
Asghar Gholami ◽  
Mohammad Shabani

In the conventional integrated navigation system, the statistical information of the process and measurement noises is considered constant. However, due to the changing dynamic environment and imperfect knowledge of the filter statistical information, the process and measurement covariance matrices are unknown and time-varying. In this paper, a multirate adaptive Kalman filter is proposed to improve the performance of the Error State Kalman Filter (ESKF) for a marine navigation system. The designed navigation system is composed of a strapdown inertial navigation system along with Doppler velocity log and inclinometer with different sampling rates. In the proposed filter, the conventional adaptive Kalman filter is modified by adaptively tuning the measurement covariance matrix of the auxiliary sensors that have varying sampling grates based on the innovation sequence. The performance of the proposed filter is evaluated using real measurements. Experimental results show that the average root mean square error of the position estimated by the proposed filter can be decreased by approximately 60% when compared to that of the ESKF.


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