A nonlinear two-filter smoothing estimation method based on DD2 filter for land vehicle POS

Self Cite

Micro Position and Orientation System (POS) is the motion compensation equipment of airborne remote sensing system, which is composed of Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) with double antennas. The INS/GNSS integrated navigation is the key technology to measure micro POS motion information. However, the installation error angle between INS and dual antennas will seriously reduce the navigation accuracy. To solve this problem, an improved integrated navigation method of micro POS based on installation error angle calibration is proposed. Firstly, the calibration method of installation error angle based on a high-precision POS and the dual antennas is presented. Then, the improved real-time navigation algorithm based on error angle compensation is established. Finally, the flight experiment results indicate that the proposed method can effectively improve the navigation accuracy compared to uncalibrated method, especially the attitude and velocity accuracies, which are improved by 36% and 27%, respectively.

Section: Introductionmentioning

confidence: 99%

Improved integrated navigation method of micro position and orientation system based on installation error angle calibration

Qu¹,

Li²,

Zhang³

2022

Self Cite

“…Shen develops a non-linear attitude observer to fuse different sensors and estimate the vehicle's attitude [11]. In order to solve the problem of non-linear error, Li proposes a non-linear two-filter smoothing estimation method for land vehicle position and orientation system [12]. The accuracy of various sensor fusion algorithms for measuring upper arm elevation relative to gravity across different motion speeds is evaluated using Kalman filter (KF) [13].…”

Section: Introductionmentioning

confidence: 99%

Vehicle platform attitude estimation method based on adaptive Kalman filter and sliding window least squares

Luo

Fan

Jiang

et al. 2020

Precision instrument measurement on an unstable platform is a difficult engineering problem, and the commonly used method is to compensate the instrument measurement results through platform attitude estimation. This paper derives a three-dimensional attitude estimation method based on inertial sensors including gyroscope and inclinometer. In order to deal with the inertial sensor noise, low-pass filter, Kalman filter, adaptive Kalman filter (AKF) and sliding window least squares (SWLS) are chosen to test the filtering performance from the frequency domain perspective. Practical filtering experiments indicate that AKF achieves the best filtering performance for gyroscope, while SWLS has the best filtering performance for inclinometer. Using AKF and SWLS to deal with inertial sensor outputs, the attitude estimation of the vehicle platform is realized. The proposed method is verified on vehicle-mounted electro-optical measurement equipment.

“…DPOS is composed of a high-precision main POS, a few low-precision slave POSs, a computer system and post-processing software [6,7]. The main POS integrates a main inertial measurement unit (IMU) and a global positioning system (GPS).…”

Section: Introductionmentioning

confidence: 99%

A multi-node synchronous baseline calibration system based on vision measurement for DPOS

Liu¹,

Wen²,

Bo³

et al. 2019

A distributed position and orientation system (DPOS) can provide abundant time-spatial information for multi-task imaging loads in the airborne earth observation system. To ensure that DPOS meets the engineering requirement, it must be accurately calibrated on the ground before DPOS can be applied to aerial remote sensing, especially baseline calibration, for which the measurement accuracy of the baseline is a key technical indicator that affects imaging accuracy. However, it is difficult to achieve baseline calibration between multiple nodes synchronously because of external interference, and there is no baseline calibration method for DPOS yet. To solve the problem mentioned above, considering the advantages of vision measurement, this paper presents a multi-node synchronous baseline calibration system for DPOS. In order to evaluate the effectiveness of the proposed system, a verification test was conducted. The measurement result of a theodolite coordinate measurement system (TCMS) is the benchmark. Under static conditions, the experimental results show that baseline measurement accuracy is better than 0.3 mm.