Improving extended Kalman filter algorithm in satellite autonomous navigation

2016 ◽  
Vol 231 (4) ◽  
pp. 743-759 ◽  
Author(s):  
Lina He ◽  
Hairui Zhou ◽  
Gongyuan Zhang
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Orbit Determination ◽  
Autonomous Navigation ◽  
Precise Orbit Determination ◽  
Satellite Orbit ◽  
Initial Position ◽  
Mean Value Theorem ◽  
Position Errors ◽  
Kalman Filter Algorithm

With the goal of reducing dependence on ground tracking systems, satellite autonomous navigation technologies are developed quickly in the recent several decades. However, precise orbit determination at high orbital altitudes is an important and challenging problem. In this paper, the nonlinear real-time orbit determination problem is investigated. Combined with satellite dynamical model, extended Kalman filter is explored to estimate satellite orbit parameters. Further, considering errors occur in linearization processing, two improvements for the extended Kalman filter algorithm, i.e. extended Kalman filter-I and extended Kalman filter-II, are proposed based on Lagrange’s mean value theorem, and respectively focus on choosing better linear expansion point and Jacobian matrix calculation point. Extensive simulations show that extended Kalman filter-I and extended Kalman filter-II significantly enhance orbit accuracy, compared with extended Kalman filter. And the increases in calculation complexity are acceptable. Finally, the robustness of extended Kalman filter-I and extended Kalman filter-II is analyzed by given different initial position errors, and results show that extended Kalman filter-I and extended Kalman filter-II have better robustness than extended Kalman filter.

scholarly journals A Discussion Related to Orbit Determination Using Nonlinear Sigma Point Kalman Filter

2009 ◽  
Vol 2009 ◽  
pp. 1-12 ◽  
Author(s):  
Paula Cristiane Pinto Mesquita Pardal ◽  
Helio Koiti Kuga ◽  
Rodolpho Vilhena de Moraes
Keyword(s):  
Kalman Filter ◽  
Dynamic Model ◽  
Extended Kalman Filter ◽  
Orbit Determination ◽  
Unscented Kalman Filter ◽  
Satellite Orbit ◽  
Observation Model ◽  
Gps Measurements ◽  
Unscented Transformation ◽  
Sigma Point

Herein, the purpose is to present a Kalman filter based on the sigma point unscented transformation development, aiming at real-time satellite orbit determination using GPS measurements. First, a brief review of the extended Kalman filter will be done. After, the sigma point Kalman filter will be introduced as well as the basic idea of the unscented transformation, in which this filter is based. Following, the unscented Kalman filter applied to orbit determination will be explained. Such explanation encloses formulations about the orbit determination through GPS; the dynamic model; the observation model; the unmodeled acceleration estimation; also an application of this new filter approaches on orbit determination using GPS measurements discussion.

scholarly journals Comparisons of CODE and CNES/CLS GPS satellite bias products and applications in Sentinel-3 satellite precise orbit determination

GPS Solutions ◽  
2021 ◽  
Vol 25 (4) ◽  
Author(s):  
Bingbing Duan ◽  
Urs Hugentobler
Keyword(s):  
Linear Combination ◽  
Orbit Determination ◽  
Fractional Part ◽  
Precise Orbit Determination ◽  
Satellite Orbit ◽  
Satellite Orbits ◽  
Satellite Clock ◽  
Analysis Center ◽  
Wide Lane ◽  
Total Difference

AbstractTo resolve undifferenced GNSS phase ambiguities, dedicated satellite products are needed, such as satellite orbits, clock offsets and biases. The International GNSS Service CNES/CLS analysis center provides satellite (HMW) Hatch-Melbourne-Wübbena bias and dedicated satellite clock products (including satellite phase bias), while the CODE analysis center provides satellite OSB (observable-specific-bias) and integer clock products. The CNES/CLS GPS satellite HMW bias products are determined by the Hatch-Melbourne-Wübbena (HMW) linear combination and aggregate both code (C1W, C2W) and phase (L1W, L2W) biases. By forming the HMW linear combination of CODE OSB corrections on the same signals, we compare CODE satellite HMW biases to those from CNES/CLS. The fractional part of GPS satellite HMW biases from both analysis centers are very close to each other, with a mean Root-Mean-Square (RMS) of differences of 0.01 wide-lane cycles. A direct comparison of satellite narrow-lane biases is not easily possible since satellite narrow-lane biases are correlated with satellite orbit and clock products, as well as with integer wide-lane ambiguities. Moreover, CNES/CLS provides no satellite narrow-lane biases but incorporates them into satellite clock offsets. Therefore, we compute differences of GPS satellite orbits, clock offsets, integer wide-lane ambiguities and narrow-lane biases (only for CODE products) between CODE and CNES/CLS products. The total difference of these terms for each satellite represents the difference of the narrow-lane bias by subtracting certain integer narrow-lane cycles. We call this total difference “narrow-lane” bias difference. We find that 3% of the narrow-lane biases from these two analysis centers during the experimental time period have differences larger than 0.05 narrow-lane cycles. In fact, this is mainly caused by one Block IIA satellite since satellite clock offsets of the IIA satellite cannot be well determined during eclipsing seasons. To show the application of both types of GPS products, we apply them for Sentinel-3 satellite orbit determination. The wide-lane fixing rates using both products are more than 98%, while the narrow-lane fixing rates are more than 95%. Ambiguity-fixed Sentinel-3 satellite orbits show clear improvement over float solutions. RMS of 6-h orbit overlaps improves by about a factor of two. Also, we observe similar improvements by comparing our Sentinel-3 orbit solutions to the external combined products. Standard deviation value of Satellite Laser Ranging residuals is reduced by more than 10% for Sentinel-3A and more than 15% for Sentinel-3B satellite by fixing ambiguities to integer values.

The p53–Mdm2 regulation relationship under different radiation doses based on the continuous–discrete extended Kalman filter algorithm

2018 ◽  
Vol 273 ◽  
pp. 230-236 ◽  
Author(s):  
Yurong Li ◽  
Jun Chen ◽  
Li Jiang ◽  
Nianyin Zeng ◽  
Haiyan Jiang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Radiation Doses ◽  
Kalman Filter Algorithm

Autonomous navigation algorithm based on AUKF filter about fusion of geomagnetic and sunlight directions

2018 ◽  
Vol 11 (4) ◽  
pp. 471-485 ◽  
Author(s):  
Bing Hua ◽  
Zhiwen Zhang ◽  
Yunhua Wu ◽  
Zhiming Chen
Keyword(s):  
Orbit Determination ◽  
Geomagnetic Field ◽  
Autonomous Navigation ◽  
Unscented Kalman Filter ◽  
Satellite Orbit ◽  
Field Vector ◽  
Low Earth Orbit ◽  
Fusion Algorithm ◽  
Content Type ◽  
Navigation Algorithm

Purpose The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy. Design/methodology/approach In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter. Findings The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy. Research limitations/implications Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors. Practical implications Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination. Originality/value This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.

Simulation of Orbit Determination of HaiYang-2 Satellite on DORIS

2013 ◽  
Vol 353-356 ◽  
pp. 3456-3459 ◽  
Author(s):  
Qiao Li Kong ◽  
Jin Yun Guo ◽  
Li Tao Han
Keyword(s):  
Orbit Determination ◽  
Tracking System ◽  
Precise Orbit Determination ◽  
Computation Time ◽  
Satellite Orbit ◽  
The World ◽  
Space Geodetic Techniques ◽  
Orbit Tracking ◽  
The Relationship

DORIS is a kind of advanced space-geodetic techniques applied in satellite orbit tracking and measuring. As the first ocean dynamic environmental satellite in China, the HY-2 satellite is equipped with the Doppler orbitography and radiopositioning integrated by satellite (DORIS) tracking system for the precise orbit determination. In particular, the investigation of our work has focused on accuracy analysis of orbit determination using simulated DORIS data given different observation noises, besides the relationship is investigated between accuracy and computation time and the number of ground beacons evenly distributed around the world. Experiment results show that observation noises can affect the accuracy of orbit determination directly, and the number of DORIS ground beacons decides the accuracy and computation time of obit determination in the condition of ground beacons are evenly distributed around the world, therefore, during the process of obit determination, we should optimize the ground beacon station distribution to achieve the best accuracy of obit determination using DORIS tracking data.

A time-efficient implementation of Extended Kalman Filter for sequential orbit determination and a case study for onboard application

2018 ◽  
Vol 62 (2) ◽  
pp. 343-358
Author(s):  
Jingshi Tang ◽  
Haihong Wang ◽  
Qiuli Chen ◽  
Zhonggui Chen ◽  
Jinjun Zheng ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Orbit Determination ◽  
Efficient Implementation

scholarly journals Distributed Orbit Determination for Global Navigation Satellite System with Inter-Satellite Link

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1031 ◽  
Author(s):  
Yuanlan Wen ◽  
Jun Zhu ◽  
Youxing Gong ◽  
Qian Wang ◽  
Xiufeng He
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Global Navigation Satellite System ◽  
Orbit Determination ◽  
Measurement Data ◽  
Satellite System ◽  
Navigation Satellite ◽  
Satellite Link ◽  
Global Navigation ◽  
Global Navigation Satellite

To keep the global navigation satellite system functional during extreme conditions, it is a trend to employ autonomous navigation technology with inter-satellite link. As in the newly built BeiDou system (BDS-3) equipped with Ka-band inter-satellite links, every individual satellite has the ability of communicating and measuring distances among each other. The system also has less dependence on the ground stations and improved navigation performance. Because of the huge amount of measurement data, the centralized data processing algorithm for orbit determination is suggested to be replaced by a distributed one in which each satellite in the constellation is required to finish a partial computation task. In the present paper, the balanced extended Kalman filter algorithm for distributed orbit determination is proposed and compared with the whole-constellation centralized extended Kalman filter, the iterative cascade extended Kalman filter, and the increasing measurement covariance extended Kalman filter. The proposed method demands a lower computation power; however, it yields results with a relatively good accuracy.

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