Satellite Navigation Signals Research Articles

Spatiotemporal Information, Near-Field Perception, and Service for Tourists by Distributed Camera and BeiDou Positioning System in Mountainous Scenic Areas

The collaborative use of camera near-field sensors for monitoring the number and status of tourists is a crucial aspect of smart scenic spot management. This paper proposes a near-field perception technical system that achieves dynamic and accurate detection of tourist targets in mountainous scenic areas, addressing the challenges of real-time passive perception and safety management of tourists. The technical framework involves the following steps: Firstly, real-time video stream signals are collected from multiple cameras to create a distributed perception network. Then, the YOLOX network model is enhanced with the CBAM module and ASFF method to improve the dynamic recognition of preliminary tourist targets in complex scenes. Additionally, the BYTE target dynamic tracking algorithm is employed to address the issue of target occlusion in mountainous scenic areas, thereby enhancing the accuracy of model detection. Finally, the video target monocular spatial positioning algorithm is utilized to determine the actual geographic location of tourists based on the image coordinates. The algorithm was deployed in the Tianmeng Scenic Area of Yimeng Mountain in Shandong Province, and the results demonstrate that this technical system effectively assists in accurately perceiving and spatially positioning tourists in mountainous scenic spots. The system demonstrates an overall accuracy in tourist perception of over 90%, with spatial positioning errors less than 1.0 m and a root mean square error (RMSE) of less than 1.14. This provides auxiliary technical support and effective data support for passive real-time dynamic precise perception and safety management of regional tourist targets in mountainous scenic areas with no/weak satellite navigation signals.

Design and experiment of Beidou satellite navigation railway tunnel coverage enhancement system

Abstract In areas of satellite navigation signals being obstructed, coveraging the interior of the tunnel with Satellite navigation signals based on navigation signals real-time regeneration technology is an important way to achieve the applications of satellite navigation in railway mobile equipment positioning and auxiliary protection for operators. We analyzed the application requirements on navigation positioning and time synchronization, and technical requirements on universality and electromagnetic compatibility, etc. The article designed the composition and logical architecture of the Beidou satellite navigation railway tunnel coverage enhancement system, proposed the design of system functions and performance parameters, and verified the system’s functionality and performance through static mode testing and dynamic mode testing. The design and implementation of the Beidou satellite navigation railway tunnel coverage enhancement system have important practical value for the application in mobile equipment positioning and auxiliary protection for operators in railway tunnel.

Assessing the ionospheric scintillations occurrence on L-band in the southern Mediterranean sector

We assess the ionospheric scintillation occurrence on Global Navigation Satellite Signals (GNSSs) over the Mediterranean sector under the rising phase of the current solar cycle. To the scope, we leverage on a network of three Ionospheric Scintillation Monitoring Receivers (ISMRs), being part of the electronic Space Weather upper atmosphere (eSWua: eswua.ingv.it) system (Pica et al., 2021). Such ISMRs are located in Lampedusa Island (Italy, Lat: 35.52°N–Lon: 12.63°E), Chania (Crete, Greece, Lat: 35.52°N, Lon: 24.04°E) and Nicosia (Cyprus, Lat: 35.18°N–Lon: 33.38°E). To our knowledge, this is the first thorough assessment of the scintillation patterns in the Southern Mediterranean sector, aimed at depicting how small-scale irregularities that form in the area can potentially affect the GNSS-based positioning and related application and services. We analyse the period from January 2021 to December 2023, reporting that the bulk of the scintillation occurrence is due to small-scale irregularities forming in the southernmost area of the field of view of the network. Irregularities of such a scale are formed during the evolution of the Rayleigh-Taylor instability featuring the Equatorial Plasma Bubbles (EPB), which may spill-over in the field of view (FoV) of the receivers, i.e. at low elevation angles in the southernmost azimuthal range. As observations at low elevation angles are subject to multipath mimic weak to moderate scintillation conditions, we focus exclusively on severe amplitude scintillation occurrence (S4 > 0.7) in the azimuthal range 110–250°, w.r.t the FoV of the receivers, subsequently reaching down to the Saharian ionosphere. To further confirm the nature of the detected GNSS scintillation occurrence, we compare the results with the Swarm Level-2 Ionospheric Bubble Index (IBI) evaluated within the same period. In the context of the April 2023 geomagnetic storm, a worst-case scenario is also documented, illustrating the potential impact of ionospheric disturbances associated with EPBs in the Southern Mediterranean area.

Angular attitude estimation algorithm using signals of Global Navigation Systems

Navigation apparatus of Global Positioning Systems are wildly used in many applications one of which is attitude determination using global satellite navigation signals, one of which is angular attitude determination. One of effective approach to this task is based on representation an object motion as linear motion along line-of-site and rotation about object center of mass. From this consideration it followed deferent tracking systems on signal parameters that connected with linear motion along line-of-site and on signal parameters that connected with rotation about object center of mass. In the article this approach is developed for synthesis of angular attitude estimation using signals of Global Navigation Systems for two-stage processing in navigation apparatus in coherent mode. Objective. To get more effective algorithm of angular attitude estimation using signals of Global Navigation Systems.

Multichannel algorithm for ambiguity resolution of combined code and phase measurements in a task of angular attitude estimation using signals of Global Navigation Systems

Navigation apparatus of Global Positioning Systems are wildly used in many applications one of which is attitude determination using global satellite navigation signals. For decision of this task there are used code and phase measurements for radiosignals received at space distribute points. It is known that phase measurements are characterized by ambiguity for resolution of which there are used different methods. Using more perfect method of ambiguity resolution one can get better angel estimation accuracy. In the article there is synthesized effective ambiguity resolution method of combined code and phase measurements using multichannel approach. Objective. To get more effective algorithm of code and phase ambiguity resolution in a task of attitude determination using global satellite navigation signals.

Improving GNSS-IR Sea Surface Height Accuracy Based on a New Ionospheric Stratified Elevation Angle Correction Model

Approximately 71% of the Earth’s surface is covered by vast oceans. With the exacerbation of global climate change, high-precision monitoring of sea surface height variations is of vital importance for constructing global ocean gravity fields and preventing natural disasters in the marine system. Global Navigation Satellite System Interferometry Reflectometry (GNSS-IR) sea surface altimetry is a method of inferring sea surface height based on the signal-to-noise ratio of satellite signals. It enables the retrieval of sea surface height variations with high precision. However, navigation satellite signals are influenced by the ionosphere during propagation, leading to deviations in the measured values of satellite elevation angles from their true values, which significantly affects the accuracy of GNSS-IR sea surface altimetry. Based on this, the contents of this paper are as follows: Firstly, a new ionospheric stratified elevation angle correction model (ISEACM) was developed by integrating the International Reference Ionosphere Model (IRI) and ray tracing methods. This model aims to improve the accuracy of GNSS-IR sea surface altimetry by correcting the ionospheric refraction effects on satellite elevation angles. Secondly, four GNSS stations (TAR0, PTLD, GOM1, and TPW2) were selected globally, and the corrected sea surface height values obtained using ISEACM were compared with observed values from tide gauge stations. The calculated average Root Mean Square Error (RMSE) and Pearson Correlation Coefficient (PCC) were 0.20 m and 0.83, respectively, indicating the effectiveness of ISEACM in sea surface height retrieval. Thirdly, a comparative analysis was conducted between sea surface height retrieval before and after correction using ISEACM. The optimal RMSE and PCC values with tide gauge station observations were 0.15 m and 0.90, respectively, representing a 20.00% improvement in RMSE and a 4.00% improvement in correlation coefficient compared to traditional GNSS-IR retrieval heights. These experimental results demonstrate that correction with ISEACM can effectively enhance the precision of GNSS-IR sea surface altimetry, which is crucial for accurate sea surface height measurements.

Principles of construction of nanosatellite radar systems based on global navigation satellite system reflectometry

Objectives. The development of radar remote sensing systems based on the reception of signals of navigation satellite systems reflected from the surface enables a constellation of nanosatellites to be deployed, in order to perform radar surveying of the Earth’s surface. The aim of this work is to develop the principles of construction of onboard bistatic remote sensing systems on nanosatellites, in order to assess the energy potential and possibilities for its increase.Methods. The optimal processing method in onboard bistatic radar systems is a development of known analytical methods of optimal processing in monostatic systems. The calculation of the energy potential is based on the experimental data obtained by other authors.Results. The utilization of signals from navigation satellite systems for surface sensing is a promising and developing area. The USA and China have deployed satellite constellations to perform remote sensing using reflected signals of navigation satellites. An algorithm for optimal processing in such systems, which realizes the principle of aperture synthesis, was developed, and the energy potential of bistatic synthetic aperture radar was calculated. In order to achieve this processing, the proposed scheme uses a standard navigation receiver to form reference signals.Conclusions. The application of optimal processing methods in bistatic radar enables a synthetic aperture based on scattered satellite navigation system signals. In order to improve the accuracy of estimates, the signal-to-noise ratio needs to be increased by combining coherent accumulation (aperture synthesis) and incoherent accumulation (aggregating measurements from different spacecraft). The signal processing methods and receiver structure proposed in this work onboard nanosatellites allow aperture synthesis to be achieved with realizable hardware requirements.

Deep Learning Soft-Decision GNSS Multipath Detection and Mitigation.

A technique is proposed to detect the presence of the multipath effect in Global Navigation Satellite Signal (GNSS) signals using a convolutional neural network (CNN) as the building block. The network is trained and validated, for a wide range of C/N0 values, with a realistic dataset constituted by the synthetic noisy outputs of a 2D grid of correlators associated with different Doppler frequencies and code delays (time-domain dataset). Multipath-disturbed signals are generated in agreement with the various scenarios encompassed by the adopted multipath model. It was found that pre-processing the outputs of the correlators grid with the two-dimensional Discrete Fourier Transform (frequency-domain dataset) enables the CNN to improve the accuracy relative to the time-domain dataset. Depending on the kind of CNN outputs, two strategies can then be devised to solve the equation of navigation: either remove the disturbed signal from the equation (hard decision) or process the pseudoranges with a weighted least-squares algorithm, where the entries of the weighting matrix are computed using the analog outputs of the neural network (soft decision).

Modeling and analysis of probabilistic characteristics of the functioning of low-channel equipment of consumers of global navigation satellite systems in conditions of signal-like interference

Formulation of the problem. A promising area of research in the field of functioning of navigation equipment for consumers of global navigation satellite signals is the development of protection of consumer equipment from the effects of simulated interference. The high availability of navigation signals of the open segment entails the threat of covert influence on consumer equipment. To date, protection measures against covert interference have been developed and applied for multi-channel consumer equipment with high computing capabilities. However, for low-channel consumer equipment, the development of such protection measures is required, for which it is necessary to determine the probabilistic characteristics of the functioning of the equipment under study under the influence of signal-like interference. Purpose. Determination of the probabilistic characteristics of the operation of multichannel navigation equipment for consumers of global navigation satellite signals in a complex interference environment. Results. A model of the functioning of consumer navigation equipment is constructed and mathematically described, the probabilistic characteristics of the functioning of consumer equipment in a complex interference environment are calculated, and the coefficient of effectiveness of signal-like interference is introduced. Practical significance. The results can be used by specialists in the field of satellite radio navigation in the development of protection systems against covert intentional exposure.

Satellite navigation signal quality monitoring algorithm based on DBO-SVM

Satellite navigation signals can provide users with accurate and continuous time and position information. Since the satellite navigation signal is susceptible to interference from terrain and other electromagnetic signals during transmission. In this study, to improve the accuracy of the traditional satellite navigation signal quality monitoring algorithm and to solve the problem of discretization in the monitoring results, the satellite navigation signal quality monitoring algorithm based on the Dung Beetle Optimization assisted Support Vector Machine (DBO-SVM) is proposed. The algorithm uses four feature quantities (correlation loss and symmetry of correlation peaks in the correlation domain, signal power in the frequency domain, eye diagram opening in the modulation domain) to classify the quality of satellite navigation signals, and optimizing the parameters of the SVM through the application of the dung beetles’ foraging mechanism. Experimental validation was conducted by simulating satellite navigation signal data, and the results indicate that the DBO-SVM algorithm is more accurate than the traditional SVM algorithm, with an accuracy rate of over 98%.

Reliable urban vehicle localization under faulty satellite navigation signals

Reliable urban navigation using global navigation satellite system requires accurately estimating vehicle position despite measurement faults and monitoring the trustworthiness (or integrity) of the estimated location. However, reflected signals in urban areas introduce biases (or faults) in multiple measurements, while blocked signals reduce the number of available measurements, hindering robust localization and integrity monitoring. This paper presents a novel particle filter framework to address these challenges. First, a Bayesian fault-robust optimization task, formulated through a Gaussian mixture model (GMM) measurement likelihood, is integrated into the particle filter to mitigate faults in multiple measurement for enhanced positioning accuracy. Building on this, a novel test statistic leveraging the particle filter distribution and the GMM likelihood is devised to monitor the integrity of the localization by detecting errors exceeding a safe threshold. The performance of the proposed framework is demonstrated on real-world and simulated urban driving data. Our localization algorithm consistently achieves smaller positioning errors compared to existing filters under multiple faults. Furthermore, the proposed integrity monitor exhibits fewer missed and false alarms in detecting unsafe large localization errors.

Effects of Equatorial Plasma Bubbles on Multi-GNSS Signals: A Case Study over South China

Equatorial plasma bubbles (EPBs) occur frequently in low-latitude areas and have a non-negligible impact on navigation satellite signals. To systematically analyze the effects of a single EPB event on multi-frequency signals of GPS, Galileo, GLONASS, and BDS, all-sky airglow images over South China are jointly used to visually determine the EPB structure and depletion degree. The results reveal that scintillations, or GNSS signal fluctuations, are directly linked to EPBs and that the intensity of scintillation is positively correlated with the airglow depletion intensity. The center of the airglow depletion often corresponds to stronger GNSS scintillation, while the edge of the bubble, which is considered to have the largest density gradient, corresponds to relatively smaller scintillation instead. This work also systematically analyzes the responses of multi-constellation and multi-frequency signals to EPBs. The results show that the L2 and L5 frequencies are more susceptible than the L1 frequency is. For different constellations, Galileo’s signal has the best tracking stability during an EPB event compared with GPS, GLONASS, and BDS. The results provide a reference for dual-frequency signal selection in precise positioning or TEC calculation, that is, L1C and L2L for GPS, L1C and L5Q for Galileo, L1P and L2C for GLONASS, and L1P and L5P for BDS. Notably, BDS-2 is significantly weaker than BDS-3. And inclined geosynchronous orbit (IGSO) satellites have abnormal data error rates, which should be related to the special signal path trajectory of the IGSO satellite.

A simulated fusion localization algorithm with adaptive error covariance matrix for closed corridor seamless positioning

Due to the blocking and reflection of buildings, the received Beidou satellite navigation signal (BDS) in the closed corridor will be getting weaker, which results in poor positioning accuracy or positioning failure. Introducing Ultra-Wide Band (UWB) positioning technology and establishing BDS/UWB integrated positioning system is an effective method to achieve seamless positioning. The positioning accuracy obtained by the Least Square-Kalman Filter (LS-KF) algorithm is below m level. However, the prior error covariance matrix of the KF correction process is easily contaminated, which affects the proportion of system observations and state prediction values to the optimal position estimation. A LS-KF fusion positioning algorithm based on adaptive error covariance matrix is proposed, the algorithm adjusts the state prior error covariance matrix by constructing an adaptive factor, improves the Kalman gain and the optimal estimation of the position, balances the trust of the filter estimation value to the observation value and the state prediction value of the integrated positioning system. Theoretical analysis and experimental results show that compared with LS-KF, EKF, UKF and improved LS-KF algorithm, the proposed LS-AKF algorithm not only has higher positioning accuracy, stronger anti-interference ability, but also has faster convergence speed.

Design of Universal Code Generator for Multi-Constellation Multi-Frequency GNSS Receiver

A multi-constellation, multi-frequency Global Navigation Satellite System (GNSS) receiver is capable of simultaneously receiving signals from multiple satellite constellations across various frequency bands. This allows for increased observations, thereby enhancing navigation accuracy, continuity, effectiveness, and reliability. The spread spectrum code structures used in satellite navigation signals differ among systems. Compatible code generators are employed in multi-constellation, multi-frequency GNSS receivers to support tasks such as signal acquisition and tracking. There are three main types of spread spectrum code structures: Linear Feedback Shift Register (LFSR), Legendre sequences, and Memory codes. The Indian Regional Navigation Satellite System (IRNSS) released the L1-SPS (Standard Positioning Service) signal format in August 2023, which utilizes the Interleaved Z4-linear ranging code (IZ4 code) as its spread spectrum code. Currently, there is no universal code generator design compatible with the IZ4 code. In this paper, a proposed universal code generator is based on the hardware structure of the IRNSS IZ4 code generator. It achieves compatibility with all LFSR-based spread spectrum codes and enables parallel generation of multiple sets of GNSS signal spread spectrum codes, thereby improving hardware utilization efficiency. The proposed structure is implemented and validated using FPGA design, and resource consumption is provided as part of the validation results.

위성 항법 신호의 순방향 오류 제어 분석

위성 항법 신호의 순방향 오류 제어 분석

Time-of-Arrival Estimation for Integrated Satellite Navigation and Communication Signals

Global navigation satellite systems (GNSSs) are used in numerous fields, but their vulnerability is a global problem that has yet to be solved. A promising way to effectively address this problem is by integrating navigation into emerging dense nongeosynchronous orbit (NGSO) megaconstellations. To maximize the downlink efficiency for users, an integrated satellite navigation and communication (ISNAC) framework is proposed in this work, in which a necessary number of packetized bursty downlink satellite communication signals are used directly for navigation purposes. Then, the user terminal estimates the time of arrival (TOA) of these ISNAC signals regardless of their coding and modulation type. To this end, a TOA estimation algorithm is proposed. Specifically, the user terminal first constructs a template signal with demodulated data bits to replicate the transmitted ISNAC signal and then calculates the cross-correlation function (CCF) of the template and the received signal for TOA estimation, based on which the TOA is finally estimated. The performance bound of the proposed TOA estimation algorithm is analyzed. Simulations are conducted to corroborate the mathematical analysis and The results show that the proposed algorithm outperforms other TOA estimators for comparsion by approaching the Cramer-Rao lower bound (CRLB) with a much lower computational complexity.

A Long Time Span-Specific Emitter Identification Method Based on Unsupervised Domain Adaptation

Specific emitter identification (SEI) is a professional technology to recognize different emitters by measuring the unique features of received signals. It has been widely used in both civilian and military fields. Recently, many SEI methods based on deep learning have been proposed, most of which assume that the training set and testing set have the same data distribution. However, in reality, the testing set is generally used later than the training set and lacks labels. The long time span may change the signal transmission environment and fingerprint features. These changes result in considerable differences in data distribution between the training and testing sets, thereby affecting the recognition and prediction abilities of the model. Therefore, the existing works cannot achieve satisfactory results for a long time span SEI. To address this challenge and obtain stable fingerprints, we transform the long time span SEI problem into a domain adaptive problem and propose an unsupervised domain adaptive method called LTS-SEI. Noteworthily, LTS-SEI uses a multilayer convolutional feature extractor to learn feature knowledge and confronts a domain discriminator to generate domain-invariant shallow fingerprints. The classifier of LTS-SEI applies feature matching to source domain samples and target domain samples to achieve the domain alignment of deep fingerprints. The classifier further reduces the intraclass diversity of deep features to alleviate the misclassification problem of edge samples in the target domain. To confirm the effectiveness and reliability of LTS-SEI, we collect multiple sets of real satellite navigation signals using two antennas with 13 m- and 40 m-large apertures, respectively, and construct two available datasets. Numerous experiments demonstrate that LTS–SEI can considerably increase the recognition accuracy of the long time span SEI and is superior to the other existing methods.

Adaptive Satellite Navigation Anti-Interference Algorithm Based on Inverse Cosine Function

Contrasting the dilemma that the traditional time-domain least mean square (LMS) algorithm in the existing satellite navigation receiver anti-interference system cannot satisfy the convergence time is short and maintain a low level of steady-state error at the same time, an inverse cosine variable step size LMS algorithm (ICVS-LMS) is proposed. To begin with, the LMS algorithm, with a fixed step size focuses on its effectiveness in attenuating and suppressing interference signals, is analyzed, and then the proposed ICVS-LMS algorithm is analyzed. In conclusion, both the ICVS-LMS algorithm and the traditional algorithm are simulated and compared in terms of their effectiveness in suppressing interference in satellite navigation signals. The experimental results demonstrate that the improved algorithm significantly reduces convergence time while maintaining a small steady-state error. The improved algorithm demonstrates high robustness and an obvious suppression effect on interference signals. The anti-interference performance is 8.41–12.22% higher than that of the proposed algorithm.

Interaction of Satellite Navigation Signals with Forest and Snow-Ice Layers

Interaction of Satellite Navigation Signals with Forest and Snow-Ice Layers

GNSS performance enhancement using measurement estimation in harsh environment.

Global navigation satellite systems (GNSSs) are commonly used to measure the position and time globally. A GNSS is convenient owing to its ability to measure accurate position relatively without using assistive tools for navigation by comparing with other sensors. Based on these benefits, the applicable area is expanding to commercial and social uses (e.g., vehicle navigation, smart grids, and smartphone apps). In the future, various services and technologies (e.g., the use of autonomous vehicles, unmanned delivery, and industrial field robots), which make Internet of Things (IOT) more active, will be used in our society. Conversely, the performance of GNSS can degrade in harsh environments, such as urban areas, owing to the property of GNSS, which calculates position and time via satellite signal reception. However, buildings in a city can block navigation satellite signals and generate multi-path errors. The blocked signals exacerbate the dilution of precision (DOP), which indicates the accuracy of the navigation solution and increases the navigation solution error. This study proposes methods to improve navigation performance by leveraging various techniques (e.g., range differences, receiver clock error hold, and virtual satellites). The methods were validated in harsh environments where visible satellites were reduced. In the simulation, each proposed method improved the navigation performance by creating an environment similar to a normal situation, despite the receiver entering a harsh environment. The results confirmed that the navigation performance deteriorated compared to the normal situation where the number of visible satellites decreased. However, the navigation performance was recovered gradually by applying the proposed techniques. Using the proposed methods, navigation performance can be maintained continuously even in situations where satellite signals are blocked.