scholarly journals A Two-Stage Kalman Filter-Based Carrier Tracking Loop for Weak GNSS Signals

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1369 ◽  
Author(s):  
Yan Cheng ◽  
Qing Chang ◽  
Hao Wang ◽  
Xianxu Li
Keyword(s):  
Kalman Filter ◽  
Satellite System ◽  
Convergence Time ◽  
Integration Time ◽  
Two Stage ◽  
Navigation Data ◽  
Coherent Integration ◽  
Tracking Loops ◽  
Coherent Integration Time ◽  
Global Navigation Satellite

For global navigation satellite system receivers, Kalman filter (KF)-based tracking loops show remarkable advantages in terms of tracking sensitivity and robustness compared with conventional tracking loops. However, to improve the tracking sensitivity further, increasing the coherent integration time is necessary, but it is typically limited by the navigation data bit sign transition. Moreover, for standard KF-based tracking receivers, the KF parameters are initialized by the acquired results. However, especially under weak signal conditions, the acquired results have frequency errors that are too large for KF-based tracking to converge rapidly to a steady state. To solve these problems, a two-stage KF-based tracking architecture is proposed to track weaker signals and achieve faster convergence. In the first stage, coarse tracking refines the acquired results and achieves bit synchronization. Then, in the second stage, fine tracking initializes the KF-based tracking by using the coarse tracking results and extends the coherent integration time without the bit sign transition limitation. This architecture not only utilizes the self-tuning technique of the KF to improve the tracking sensitivity, but also adopts the two-stage to reduce the convergence time of the KF-based tracking. Simulation results demonstrate that the proposed method outperforms conventional tracking techniques in terms of tracking sensitivity. Furthermore, the proposed method is compared with the standard KF-based tracking approach, proving that the proposed method converges more rapidly.

scholarly journals Signal-to-Noise Ratio Analyses of Spaceborne GNSS-Reflectometry from Galileo and BeiDou Satellites

2021 ◽  
Vol 14 (1) ◽  
pp. 35
Author(s):  
Yang Nan ◽  
Shirong Ye ◽  
Jingnan Liu ◽  
Bofeng Guo ◽  
Shuangcheng Zhang ◽  
...  
Keyword(s):  
Global Navigation Satellite System ◽  
Signal To Noise Ratio ◽  
Satellite System ◽  
Integration Time ◽  
Navigation Satellite ◽  
Signal To Noise ◽  
Coherent Integration ◽  
Global Navigation ◽  
Coherent Integration Time ◽  
Global Navigation Satellite

In recent years, Global Navigation Satellite System Reflectometry (GNSS-R) technology has made considerable progress with the increasing of GNSS-R satellites in orbit, the improvements of GNSS-R data processing technology, and the expansion of its geophysical applications. Meanwhile, with the modernization and evolution of GNSS systems, more signal sources and signal modulation modes are available. The effective use of the signals at different frequencies or from new GNSS systems can improve the accuracy, reliability, and resolution of the GNSS-R data products. This paper analyses the signal-to-noise ratio (SNR) of the GNSS-R measurements from Galileo and BeiDou-3 (BDS-3) systems, which is one of the important indicators to measure the quality of GNSS-R data. The multi-GNSS (GPS, Galileo and BDS-3) complex waveform products generated from the raw intermediate frequency data from TechDemoSat-1 (TDS-1) satellite and Cyclone Global Navigation Satellite System (CYGNSS) constellation are used for such analyses. The SNR and normalized SNR (NSNR) of the reflected signals from Galileo and BDS-3 satellites are compared to these from GPS. Preliminary results show that the GNSS-R SNRs from Galileo and BDS-3 are ∼1–2 dB lower than the GNSS-R measurements from GPS, which could be due to the power of the transmitted power and the bandwidth of the receiver. In addition, the effect of coherent integration time on GNSS-R SNR is also assessed for different GNSS signals. It is shown that the SNR of the reflected signals can be improved by using longer coherent integration time (∼0.4–0.8 dB with 2 ms coherent integration and ∼0.6–1.2 dB with 4 ms coherent integration). In addition, it is also shown that the SNR can be improved more efficiently (∼0.2–0.4 dB) for reflected BDS-3 and Galileo signals than for GPS. These results can provide useful references for the design of future spaceborne GNSS-R instrument compatible with reflections from multi-GNSS constellations.

scholarly journals Joint Acquisition Estimator of Modern GNSS Tiered Signals Using Block Pre-Correlation Processing of Secondary Code

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2965
Author(s):  
Jiří Svatoň ◽  
František Vejražka
Keyword(s):  
Search Algorithm ◽  
Global Navigation Satellite Systems ◽  
Integration Time ◽  
Zero Padding ◽  
Satellite Systems ◽  
Coherent Integration ◽  
Correlation Processing ◽  
Single Block ◽  
Coherent Integration Time ◽  
Global Navigation Satellite

Objective is a joint primary and secondary code (SC) acquisition estimator of tiered Global Navigation Satellite Systems (GNSS) signals. The estimator is based on the Parallel Code Search algorithm (PCS) combined with the Single-Block-Zero-Padding (SBZP) and the Pre-correlation Coherent Accumulation (PCA). The PCA realizes the extension of the coherent integration time in front of the PCS. However, the PCS with the SBZP and the PCA is affected by a navigation/SC bit transition problem due to its cyclic property of a computed Cross-Ambiguity Function (CAF). This CAF is degraded by diverse parasitic fragments and is not directly applicable for an acquisition. A novel analysis of this mechanism and its impact is presented. Then, the proposed modified SBZP (mSBZP) modified PCA (mPCA) PCS estimator is constructed, which does not degrade the CAF. The mSBZP allows the use of the PCS algorithm in the presence of SC bit transition, while the mPCA decreases the number of PCS algorithm calculations by a factor of SC chip count due to SC pre-correlation processing. The algorithm has the same detection performance in comparison with conventional Double-Block-Zero-Padding (DBZP). However, it allows using the PCS of half-length with longer latency up to a factor of SC chip count.

Galileo E5 Signal Acquisition using Intermediate Coherent Integration Time

2019 ◽  
Vol 72 (3) ◽  
pp. 555-574
Author(s):  
Jérôme Leclère ◽  
René Landry
Keyword(s):  
Partial Correlation ◽  
Correlation Method ◽  
Satellite System ◽  
Integration Time ◽  
Signal Acquisition ◽  
Coherent Integration ◽  
L5 Signal ◽  
Galileo E5 ◽  
Low Sensitivity ◽  
Global Navigation Satellite

The acquisition of modern Global Navigation Satellite System (GNSS) signals may be difficult due to the presence of a secondary code. Indeed, short coherent integration times should be used without non-coherent integration, which implies a low sensitivity; or long coherent integration times should be used, requiring synchronisation with the secondary code and thus a full correlation, which implies a significant computational burden, especially for signals with long secondary codes such as the Galileo E5 signal. A third option that lies between the previous two is to perform a partial correlation using less than one secondary code period as input, however this is less efficient in terms of complexity than using an entire secondary code period, and the code's autocorrelation properties are completely changed. The authors recently proposed a method based on combining secondary code correlations, allowing the use of intermediate coherent integration times with the possibility to do non-coherent integrations, and the method was successfully applied to the Global Positioning System (GPS) L5 signal. This paper studies the application of the method to the Galileo E5 signal, compares it with the partial correlation method, and discusses the case where less than one secondary code period is used as an input

scholarly journals PERFORMANCE OF GNSS CARRIER-TRACKING LOOP BASED ON KALMAN FILTER IN A CHALLENGING ENVIRONMENT

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1687-1693 ◽  
Author(s):  
Y. Luo ◽  
C. Yu ◽  
J. Li ◽  
N. El-Sheimy
Keyword(s):  
Kalman Filter ◽  
Model Simulation ◽  
Random Noise ◽  
Dynamic Environment ◽  
Satellite System ◽  
Phase Lock Loop ◽  
Integration Time ◽  
Loop Model ◽  
Tracking Loop ◽  
Coherent Integration

<p><strong>Abstract.</strong> The global navigation satellite system (GNSS) recently plays an extremely important role in positioning, navigation, and timing (PNT) applications for the modernized automations and mechanizations, e.g., unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), military aircrafts, etc. Nevertheless, GNSS signals are very vulnerable to the influence of various interferences when they are received on Earth, and the reason why it happens is that the long line-of-sight (LOS) distance between the satellite and the receiver user dramatically reduces the power strength after the signal reaches at the ground. The weak GNSS signal is hard to be handled with traditional phase lock loop (PLL), especially in a dynamic environment. Again, the trade-off among the coherent integration time of tracking loop, received signal power strength, and signal or user receiver dynamics is still a tough and remained problem to be solved. The Kalman filter (KF) is always a promising tool to efficiently decrease the random noise for the tracking process. In our work, we evaluate the performances of the tracking loop modelled with both standard KF and extended Kalman filter (EKF). An adaptive algorithm for the covariance matrix of the process noise is contained in our system to increase the tracking ability in a weak and dynamic environment. Besides, a noise channel is also contained to automatically adjust the priori measurement covariance for the KF tracking loop model. Simulation results demonstrate the performance with the proposed technique.</p>

scholarly journals Galileo L10 Satellites: Orbit, Clock and Signal-in-Space Performance Analysis

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1695
Author(s):  
Constantin-Octavian Andrei ◽  
Sonja Lahtinen ◽  
Markku Poutanen ◽  
Hannu Koivula ◽  
Jan Johansson
Keyword(s):  
Performance Indicators ◽  
Satellite System ◽  
Short Term ◽  
Orbital Inclination ◽  
Navigation Data ◽  
Periodic Signals ◽  
Global Navigation Satellite ◽  
Minor Correction ◽  
Very High

The tenth launch (L10) of the European Global Navigation Satellite System Galileo filled in all orbital slots in the constellation. The launch carried four Galileo satellites and took place in July 2018. The satellites were declared operational in February 2019. In this study, we report on the performance of the Galileo L10 satellites in terms of orbital inclination and repeat period parameters, broadcast satellite clocks and signal in space (SiS) performance indicators. We used all available broadcast navigation data from the IGS consolidated navigation files. These satellites have not been reported in the previous studies. First, the orbital inclination (56.7±0.15°) and repeat period (50680.7±0.22 s) for all four satellites are within the nominal values. The data analysis reveals also 13.5-, 27-, 177- and 354-days periodic signals. Second, the broadcast satellite clocks show different correction magnitude due to different trends in the bias component. One clock switch and several other minor correction jumps have occurred since the satellites were declared operational. Short-term discontinuities are within ±1 ps/s, whereas clock accuracy values are constantly below 0.20 m (root-mean-square—rms). Finally, the SiS performance has been very high in terms of availability and accuracy. Monthly SiS availability has been constantly above the target value of 87% and much higher in 2020 as compared to 2019. Monthly SiS accuracy has been below 0.20 m (95th percentile) and below 0.40 m (99th percentile). The performance figures depend on the content and quality of the consolidated navigation files as well as the precise reference products. Nevertheless, these levels of accuracy are well below the 7 m threshold (95th percentile) specified in the Galileo service definition document.

scholarly journals Opportunistic In-Flight INS Alignment Using LEO Satellites and a Rotatory IMU Platform

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 280
Author(s):  
Farzan Farhangian ◽  
Hamza Benzerrouk ◽  
Rene Landry
Keyword(s):  
Kalman Filter ◽  
State Space Model ◽  
Flight Test ◽  
Satellite System ◽  
Low Earth Orbit ◽  
Measurement Unit ◽  
Starting Point ◽  
Leo Satellites ◽  
Positioning Method ◽  
Global Navigation Satellite

With the emergence of numerous low Earth orbit (LEO) satellite constellations such as Iridium-Next, Globalstar, Orbcomm, Starlink, and OneWeb, the idea of considering their downlink signals as a source of pseudorange and pseudorange rate measurements has become incredibly attractive to the community. LEO satellites could be a reliable alternative for environments or situations in which the global navigation satellite system (GNSS) is blocked or inaccessible. In this article, we present a novel in-flight alignment method for a strapdown inertial navigation system (SINS) using Doppler shift measurements obtained from single or multi-constellation LEO satellites and a rotation technique applied on the inertial measurement unit (IMU). Firstly, a regular Doppler positioning algorithm based on the extended Kalman filter (EKF) calculates states of the receiver. This system is considered as a slave block. In parallel, a master INS estimates the position, velocity, and attitude of the system. Secondly, the linearized state space model of the INS errors is formulated. The alignment model accounts for obtaining the errors of the INS by a Kalman filter. The measurements of this system are the difference in the outputs from the master and slave systems. Thirdly, as the observability rank of the system is not sufficient for estimating all the parameters, a discrete dual-axis IMU rotation sequence was simulated. By increasing the observability rank of the system, all the states were estimated. Two experiments were performed with different overhead satellites and numbers of constellations: one for a ground vehicle and another for a small flight vehicle. Finally, the results showed a significant improvement compared to stand-alone INS and the regular Doppler positioning method. The error of the ground test reached around 26 m. This error for the flight test was demonstrated in different time intervals from the starting point of the trajectory. The proposed method showed a 180% accuracy improvement compared to the Doppler positioning method for up to 4.5 min after blocking the GNSS.

scholarly journals Multi-GNSS Combined Precise Point Positioning Using Additional Observations with Opposite Weight for Real-Time Quality Control

2019 ◽  
Vol 11 (3) ◽  
pp. 311 ◽  
Author(s):  
Wenju Fu ◽  
Guanwen Huang ◽  
Yuanxi Zhang ◽  
Qin Zhang ◽  
Bobin Cui ◽  
...  
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Precise Point Positioning ◽  
Satellite System ◽  
Convergence Time ◽  
Navigation Satellite ◽  
Positioning Accuracy ◽  
Global Navigation ◽  
Point Positioning ◽  
Global Navigation Satellite

The emergence of multiple global navigation satellite systems (multi-GNSS), including global positioning system (GPS), global navigation satellite system (GLONASS), Beidou navigation satellite system (BDS), and Galileo, brings not only great opportunities for real-time precise point positioning (PPP), but also challenges in quality control because of inevitable data anomalies. This research aims at achieving the real-time quality control of the multi-GNSS combined PPP using additional observations with opposite weight. A robust multiple-system combined PPP estimation is developed to simultaneously process observations from all the four GNSS systems as well as single, dual, or triple systems. The experiment indicates that the proposed quality control can effectively eliminate the influence of outliers on the single GPS and the multiple-system combined PPP. The analysis on the positioning accuracy and the convergence time of the proposed robust PPP is conducted based on one week’s data from 32 globally distributed stations. The positioning root mean square (RMS) error of the quad-system combined PPP is 1.2 cm, 1.0 cm, and 3.0 cm in the east, north, and upward components, respectively, with the improvements of 62.5%, 63.0%, and 55.2% compared to those of single GPS. The average convergence time of the quad-system combined PPP in the horizontal and vertical components is 12.8 min and 12.2 min, respectively, while it is 26.5 min and 23.7 min when only using single-GPS PPP. The positioning performance of the GPS, GLONASS, and BDS (GRC) combination and the GPS, GLONASS, and Galileo (GRE) combination is comparable to the GPS, GLONASS, BDS and Galileo (GRCE) combination and it is better than that of the GPS, BDS, and Galileo (GCE) combination. Compared to GPS, the improvements of the positioning accuracy of the GPS and GLONASS (GR) combination, the GPS and Galileo (GE) combination, the GPS and BDS (GC) combination in the east component are 53.1%, 43.8%, and 40.6%, respectively, while they are 55.6%, 48.1%, and 40.7% in the north component, and 47.8%, 40.3%, and 34.3% in the upward component.

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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