DESC:POSITIONING SYSTEM TO DETECT AND RECOVER SPOOFING OF GLOBAL NAVIGATION SATELLITE SIGNALS
CROSS REFERENCE TO RELATED APPLICTIONS
The present application claims priority from Indian Provisional Patent Application No. 202421026805 filed on 31/03/2025, the entirety of which is incorporated herein by a reference.
TECHNICAL FIELD
The present disclosure generally relates to satellite-based positioning systems. Further, the present disclosure particularly relates to a positioning system to detect and recover spoofing of global navigation satellite signals.
BACKGROUND
Satellite-based positioning technique has become an important component of modern navigation and geolocation applications. Further, global navigation satellite systems (GNSS) are widely employed for civilian and military applications, comprising aviation, maritime navigation, land-based transportation, surveying, and accurate timing applications. Furthermore, GNSS receivers acquire signals from space vehicles to determine accurate location information. Various techniques have been developed to improve the reliability and accuracy of GNSS-based positioning systems. However, such systems are vulnerable to various forms of signal interference, comprising unintentional radio frequency interference and intentional attacks like jamming and spoofing.
Further, spoofing of GNSS signals involves transmitting false signals to deceive a GNSS receiver into computing incorrect location information. Spoofing attacks can be performed using signal generators which mimic genuine GNSS signals, leading to false positioning data. Various techniques have been developed to mitigate spoofing attacks. One well-known approach involves signal authentication mechanisms which utilize cryptographic techniques to verify the authenticity of received signals. However, said authentication mechanisms require modifications to existing GNSS infrastructure and receiver hardware, which limit widespread implementation. Moreover, cryptographic-based authentication techniques increase computational complexity, leading to delays in position determination.
Another known approach employs signal anomaly detection based on characteristics for example signal strength, Doppler shift, and signal arrival time. By analysing signal inconsistencies, anomalies associated with spoofing attacks can be detected. However, said methods are ineffective against spoofing attacks which replicate signal parameters of legitimate GNSS signals with high accuracy. Moreover, reliance on signal strength variations makes detection unreliable in urban environments where multipath effects cause signal fluctuations.
Further, another technique utilizes receiver autonomous integrity monitoring (RAIM) to cross-check measurements from multiple satellites to identify inconsistencies. RAIM is commonly used in aviation applications to improve GNSS reliability. However, RAIM depends on a sufficient number of satellite signals to detect faults, which may not be available in challenging environments for example urban canyons or under dense foliage. Additionally, RAIM techniques do not provide robust countermeasures to mitigate spoofing attacks but only identify discrepancies.
Moreover, ground-based augmentation systems (GBAS) and satellite-based augmentation systems (SBAS) have been implemented to improve GNSS accuracy and integrity by providing correction signals. GBAS relies on fixed reference stations which transmit differential correction data, while SBAS utilizes geostationary satellites to broadcast correction information. However, said augmentation systems do not specifically address spoofing threats and may themselves be vulnerable to signal manipulation.
Furthermore, machine learning-based techniques have been explored for GNSS spoofing detection, utilizing pattern recognition to identify anomalies in received signals. While said techniques improve spoofing detection capabilities, real-time implementation is challenging due to high computational demands and dependency on training datasets representative of all possible spoofing scenarios. Additionally, machine learning models require continuous updates to maintain effectiveness against evolving spoofing techniques.
In light of the above discussion, there exists an urgent need for solutions that overcome problems associated with conventional systems and techniques for detecting and recovering spoofing of global navigation satellite signals.
SUMMARY
The aim of the present disclosure is to provide a positioning system to detect and recover spoofing of global navigation satellite signals. The positioning system aims to improve the accuracy and reliability of location determination by identifying discrepancies caused by spoofed signals and mitigating threats associated with manipulated navigation signals.
The present disclosure relates to a positioning system to detect and recover spoofing of global navigation satellite signals. The positioning system comprises a user equipment. The user equipment comprises a global navigation satellite system (GNSS) receiver which receives navigation signals from multiple space vehicles and extracts location data from the received navigation signals. A reference structure associated with a predetermined location transmits a location message indicative of the predetermined location. A processing unit communicatively linked to the user equipment and the reference structure acquires the extracted location data and the location message, calculates a location of the user equipment based on the acquired location data and location message, and compares the calculated location with the predetermined location of the reference structure to generate a discrepancy value. A spoofing detection unit operatively coupled to the processing unit identifies a spoof indication of GNSS when the generated discrepancy value exceeds a predefined threshold.
Further, the user equipment receives assistance data from a location server to improve the accuracy of the extracted location data. The location server generates a confidence score indicating the reliability of the calculated location of the user equipment, stores historical location data for movement pattern analysis, and communicates with a network for remote location determination. Furthermore, the processing unit assesses variations in signal propagation characteristics to identify potential anomalies in location data. Additionally, the user equipment communicates with an external client for real-time location tracking, navigation assistance, or emergency response applications. The user equipment also estimates an uncertainty value for the extracted location data based on satellite signal strength and environmental interference. The user equipment establishes communication with base stations or access points to obtain supplementary location information.
Furthermore, the GNSS receiver compares Doppler shift variations in the received navigation signals to determine inconsistencies indicative of anomalous transmission sources. Additionally, the spoofing detection unit analyzes sudden jumps in calculated location exceeding predefined kinematic movement limits as an indication of GNSS spoofing, compares time-drift anomalies in the received navigation signals to identify inconsistencies caused by artificially synchronized spoofing sources, cross-checks GNSS time-stamp variations against a stored internal atomic clock reference to detect spoofing attacks, and classifies detected spoofing events into at least one of signal replay, power-controlled deception, or phase-manipulated spoofing based on observed signal anomalies.
In another aspect, the present disclosure provides a method for detecting and recovering spoofing of global navigation satellite signals. The method comprises receiving navigation signals from multiple space vehicles, extracting location data from the received navigation signals, transmitting a location message indicative of a predetermined location from a reference structure, acquiring extracted location data and the location message, calculating a location based on the acquired location data and location message, comparing the calculated location with the predetermined location of the reference structure to generate a discrepancy value, and identifying a spoof indication of GNSS when the generated discrepancy value exceeds a predefined threshold.
Further, the processing unit adjusts the predefined threshold based on the propagation conditions of detected global navigation satellite signals. The processing unit generates an alert message when a spoof indication of GNSS is detected, wherein the alert message is transmitted to an external monitoring system. Furthermore, the spoofing detection unit stores detected spoof indications in a historical database for pattern recognition analysis. Additionally, the processing unit integrates GNSS signal authenticity verification with an external reference signal repository for real-time validation. The positioning system applies adaptive thresholding techniques to adjust spoof detection sensitivity based on real-time environmental conditions.
BRIEF DESCRIPTION OF DRAWINGS
The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.
Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:
FIG. 1 illustrates a positioning system 100 to detect and recover spoofing of the global navigation satellite signals (GNSS), in accordance with embodiments of the present disclosure;
FIG. 2 illustrates a method for detecting and recovering spoofing of the global navigation satellite signals, in accordance with embodiments of the present disclosure;
FIG. 3 illustrates a state diagram of the positioning system 100 for detecting and recovering spoofing of global navigation satellite signals, in accordance with embodiments of the present disclosure; and
FIG. 4 illustrates a schematic diagram of signal reception and spoofing detection, in accordance with the embodiments of the present disclosure.
In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.
DETAILED DESCRIPTION
The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognise that other embodiments for carrying out or practising the present disclosure are also possible.
The description set forth below in connection with the appended drawings is intended as a description of certain embodiments of a positioning system to detect and recover spoofing of the global navigation satellite signals and is not intended to represent the only forms that may be developed or utilised. The description sets forth the various structures and/or functions in connection with the illustrated embodiments; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimised to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.
While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.
In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings, and which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
The present disclosure will be described herein below with reference to the accompanying drawings. In the following description, well known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.
As used herein, the term "positioning system" is used to refer to a system which determines a geographical location by utilizing signals from satellite-based navigation systems. Said system may comprise various components which receive, process, and validate navigation signals to provide an accurate location estimate. Additionally, the positioning system may employ techniques to detect inconsistencies in the received signals to identify potential anomalies in location data. The positioning system may be applied across various fields, comprising transportation, defense, emergency response, and geospatial mapping. Further, the positioning system may incorporate multiple methods of validation, comprising cross-referencing received signals with known reference points, analyzing signal propagation characteristics, and comparing calculated locations with predetermined locations. The positioning system may function independently or in conjunction with external communication networks, base stations, or supplementary data sources to improve accuracy and reliability. The positioning system may be implemented in mobile devices, automotive navigation systems, and infrastructure monitoring applications.
As used herein, the term "user equipment" is used to refer to an electronic device which receives navigation signals from satellite-based navigation systems and determines a corresponding location. Such user equipment may comprise mobile devices, wearable devices, vehicle-mounted units, or embedded systems in transportation infrastructure. The user equipment may acquire signals from multiple space vehicles and process the received data to extract location-related information. The user equipment may communicate with external data sources, comprising reference structures, base stations, or cloud-based services, to improve location determination. The user equipment may operate in urban, suburban, or remote environments and may compensate for signal disturbances caused by environmental factors. The user equipment may also incorporate additional sensors, for example accelerometers, gyroscopes, or magnetometers, to supplement satellite-based positioning data. The user equipment may support real-time or periodic location updates for navigation, tracking, or emergency response applications.
As used herein, the term "global navigation satellite system (GNSS) receiver" is used to refer to a component within user equipment which receives signals transmitted by multiple space vehicles forming part of a satellite-based navigation system. The GNSS receiver extracts location data by analyzing received signals, comprising parameters for example signal timing, frequency, and phase. The GNSS receiver may support multiple satellite constellations, for example GPS, GLONASS, Galileo, or BeiDou, to improve positioning accuracy and reliability. The GNSS receiver may also perform error correction techniques, comprising atmospheric delay compensation and multipath mitigation. The GNSS receiver may integrate with additional sensors to improve location accuracy in environments with limited satellite visibility. The GNSS receiver may operate in real-time to provide continuous location tracking or periodically acquire location updates based on application requirements.
As used herein, the term "reference structure" is used to refer to an entity associated with a predetermined location which transmits a location message indicative of the predetermined location. The reference structure may comprise ground-based infrastructure, beacon transmitters, or fixed-position devices which serve as known reference points for location validation. The reference structure may communicate with user equipment by broadcasting signals containing location-identifying information. The reference structure may assist in detecting inconsistencies between calculated locations and known locations to identify potential anomalies in navigation data. The reference structure may be positioned in areas with high navigation signal interference or spoofing risk to improve location verification. The reference structure may be integrated into existing communication networks or deployed as standalone units in strategic locations. The reference structure may operate continuously or at predefined intervals based on application requirements.
As used herein, the term "processing unit" is used to refer to an electronic component which acquires, processes, and analyzes location data received from user equipment and reference structures. The processing unit may be implemented as a microcontroller, microprocessor, or embedded computing system. The processing unit calculates a location based on extracted location data and location messages obtained from the reference structure. The processing unit compares the calculated location with the predetermined location of the reference structure to generate a discrepancy value. The processing unit may employ statistical analysis, machine learning models, or signal processing techniques to assess variations in location data. The processing unit may also communicate with external data sources to refine location estimates and improve detection accuracy. The processing unit may adjust detection sensitivity based on environmental conditions and historical navigation data. The processing unit may operate in real-time or perform batch processing for post-analysis.
As used herein, the term "spoofing detection unit" is used to refer to an electronic component which analyzes location data discrepancies to identify a spoof indication of GNSS signals. The spoofing detection unit evaluates variations in navigation signal characteristics, for example sudden jumps in calculated location, time-drift anomalies, or inconsistencies in Doppler shift measurements. The spoofing detection unit may apply predefined thresholds to distinguish genuine navigation signals from manipulated transmissions. The spoofing detection unit may cross-check navigation timestamps against internal clock references to detect artificially synchronized spoofing sources. The spoofing detection unit may classify detected spoofing events into various categories, comprising signal replay, power-controlled deception, or phase-manipulated spoofing. The spoofing detection unit may store detected spoof indications in a historical database for pattern recognition analysis. The spoofing detection unit may generate alerts or trigger corrective actions upon detecting spoofing attempts. The spoofing detection unit may operate autonomously or in conjunction with external monitoring systems.
FIG. 1 illustrates a positioning system 100 to detect and recover spoofing of the global navigation satellite signals, in accordance with embodiments of the present disclosure. The positioning system 100 comprises a user equipment 102 that contains a global navigation satellite signal (GNSS) receiver 104 which receives navigation signals from a plurality of space vehicles and extracts location data based on the received navigation signals. The user equipment 102 may comprise one or more antennas to facilitate reception of navigation signals transmitted from the space vehicles. The GNSS receiver 104 processes the received navigation signals by demodulating signal parameters, comprising timing, frequency, and phase characteristics. The GNSS receiver 104 may support multiple satellite constellations, comprising GPS, GLONASS, Galileo, or BeiDou, to improve reliability in diverse geographic regions. The GNSS receiver 104 applies error correction techniques to compensate atmospheric delays, ionospheric effects, and multipath interference. The GNSS receiver 104 may incorporate additional sensors, comprising accelerometers, gyroscopes, or magnetometers, to supplement navigation data in environments with limited satellite visibility. The user equipment 102 may comprise a memory component to store received signal data and location-related information. The user equipment 102 may communicate with external systems through wired or wireless communication interfaces to exchange supplementary data related to location determination. The user equipment 102 may be deployed in mobile devices, vehicles, or infrastructure to support positioning applications.
In an embodiment, the positioning system 100 comprises a reference structure 106 that is associated with a predetermined location and transmits a location message indicative of the predetermined location. The reference structure 106 may be a fixed infrastructure component, a ground-based beacon, or a transmission device which operates within a known geographical area. The reference structure 106 broadcasts the location message using wireless communication techniques, comprising radio frequency transmission, optical signals, or low-power wide-area network communication. The reference structure 106 may comprise a timing synchronization mechanism to align transmitted messages with GNSS timestamps. The reference structure 106 may be positioned in areas where navigation signal integrity verification is required, comprising urban environments, transportation hubs, or important infrastructure locations. The reference structure 106 may communicate with a central control system to update transmitted location messages dynamically. The reference structure 106 may operate continuously or at predefined intervals based on application requirements.
In an embodiment, the positioning system 100 comprises a processing unit 108 that is communicatively linked to the user equipment 102 and the reference structure 106 and acquires extracted location data and the location message. The processing unit 108 calculates a location of the user equipment 102 based on the acquired location data and the acquired location message. The processing unit 108 compares the calculated location with the predetermined location of the reference structure 106 to generate a discrepancy value. The processing unit 108 may be implemented as a microprocessor, a field-programmable gate array, or an application-specific integrated circuit capable of executing location analysis operations. The processing unit 108 may apply statistical analysis techniques to evaluate location discrepancies and determine variations caused by signal inconsistencies. The processing unit 108 may store historical location data to perform trend analysis and improve detection accuracy. The processing unit 108 may communicate with external databases or monitoring systems to retrieve reference data for comparison with real-time location information. The processing unit 108 may adjust sensitivity parameters for discrepancy value generation based on environmental conditions and signal propagation characteristics. The processing unit 108 may operate autonomously or under supervisory control from a central monitoring system.
In an embodiment, the positioning system 100 comprises a spoofing detection unit 110 that is operatively coupled to the processing unit 108 and identifies a spoof indication of GNSS when the generated discrepancy value exceeds a predefined threshold. The spoofing detection unit 110 analyzes received location data and identifies anomalies indicative of signal manipulation. The spoofing detection unit 110 evaluates sudden variations in calculated location, signal timing inconsistencies, or unexpected Doppler shift patterns to detect spoofing attempts. The spoofing detection unit 110 may utilize cross-referencing techniques to validate navigation timestamps against stored reference clock values. The spoofing detection unit 110 may classify detected spoofing events into different categories, comprising signal replay attacks, power-controlled deception, or phase-manipulated spoofing. The spoofing detection unit 110 may store detected spoof indications in a historical database for subsequent pattern recognition analysis. The spoofing detection unit 110 may generate alert notifications or trigger countermeasures upon detecting spoofing incidents. The spoofing detection unit 110 may communicate with remote monitoring centers for centralized threat assessment and response coordination.
In an embodiment, the user equipment 102 may receive assistance data from a location server to improve the accuracy of extracted location data. The assistance data may comprise satellite ephemeris information, atmospheric correction parameters, differential corrections, or augmentation data which refine the positioning accuracy of the user equipment 102. The location server may communicate with multiple satellite navigation systems and ground-based reference stations to collect real-time navigation data. The assistance data may be transmitted to the user equipment 102 through cellular networks, Wi-Fi, or dedicated communication channels. The user equipment 102 may process the assistance data in combination with received navigation signals to reduce position errors caused by ionospheric disturbances, multipath interference, or satellite clock inaccuracies. The user equipment 102 may request assistance data periodically or based on environmental conditions affecting signal reception. The assistance data may be dynamically updated by the location server to account for real-time variations in satellite positions and atmospheric conditions.
In an embodiment, the location server may generate a confidence score indicating the reliability of a calculated location of the user equipment 102. The confidence score is computed based on multiple parameters, comprising signal strength, number of satellites in view, satellite geometry, and historical positioning accuracy. The location server stores historical location data for movement pattern analysis, allowing for long-term tracking of user equipment 102 movement trends. The historical data enables the identification of anomalies in movement behavior which may indicate spoofing or signal manipulation. The location server communicates with a network for remote location determination by exchanging data with external geolocation databases, monitoring systems, or mapping services. The network communication enables continuous verification of location accuracy by cross-referencing reported positions with known reference points. The location server may also share confidence scores and movement analysis data with authorized monitoring systems to improve situational awareness and threat detection.
In an embodiment, the processing unit 108 may assess variations in signal propagation characteristics to identify potential anomalies in location data. The variations may comprise unexpected delays in signal arrival time, abnormal fluctuations in signal-to-noise ratios, or inconsistencies in Doppler shift measurements. The processing unit 108 compares real-time navigation data with stored reference models to detect deviations indicative of interference or spoofing. The processing unit 108 may apply statistical filtering techniques to differentiate between natural environmental effects and artificial signal alterations. The processing unit 108 may analyze received navigation signals in combination with supplementary data from external sensors, comprising barometric altimeters, accelerometers, or gyroscopes, to validate location accuracy. The processing unit 108 may continuously monitor signal integrity parameters and adjust detection thresholds based on prevailing atmospheric and environmental conditions. The processing unit 108 may store detected anomalies in a database for further analysis or future reference in pattern recognition models.
In an embodiment, the user equipment 102 may communicate with an external client for real-time location tracking, navigation assistance, or emergency response applications. The external client may be a mobile device, a monitoring center, or a cloud-based navigation service which receives location updates from the user equipment 102. The communication may be established through cellular networks, satellite communication, or short-range wireless techniques. The external client processes received location data to provide turn-by-turn navigation guidance, route optimization, or geofencing alerts. The communication with the external client may be continuous or event-triggered based on predefined conditions for example movement outside a described area or sudden changes in location coordinates. The user equipment 102 may transmit periodic status updates to the external client to enable remote monitoring of real-time movement patterns. The external client may generate alerts or notifications based on location changes to support time-sensitive decision-making processes.
In an embodiment, the user equipment 102 may estimate an uncertainty value for extracted location data based on satellite signal strength and environmental interference. The uncertainty value represents the expected deviation between calculated and actual location coordinates. The uncertainty value is derived from multiple factors, comprising the number of available satellites, geometric dilution of accuracy, atmospheric interference, and signal obstructions caused by buildings or terrain. The user equipment 102 evaluates real-time signal conditions and dynamically adjusts uncertainty estimates to reflect prevailing navigation accuracy. The uncertainty value may be used to determine the reliability of location measurements and filter out erroneous position fixes. The user equipment 102 may integrate uncertainty values into location reporting mechanisms to provide contextual accuracy information to external monitoring systems. The uncertainty value may be stored in a historical database to analyze long-term positioning trends and assess environmental impacts on navigation performance.
In an embodiment, the user equipment 102 may establish communication with base stations or access points to obtain supplementary location information. The base stations may comprise cellular towers, Wi-Fi routers, or dedicated positioning beacons which provide alternative geolocation data. The supplementary location information may be used in conjunction with satellite-based navigation data to improve accuracy, particularly in areas with poor satellite visibility. The user equipment 102 may perform network-based positioning techniques for example triangulation, time-of-arrival analysis, or received signal strength measurements to refine location estimates. The user equipment 102 may prioritize data sources based on signal reliability and environmental conditions to optimize accuracy. The communication with base stations may be continuous or initiated on-demand when satellite signals are degraded. The user equipment 102 may combine base station-derived location data with onboard sensor measurements to improve positioning performance in complex urban environments or indoor settings.
In an embodiment, the GNSS receiver 104 may compare Doppler shift variations in received navigation signals to determine inconsistencies indicative of anomalous transmission sources. The Doppler shift variations result from relative motion between the user equipment 102 and the space vehicles transmitting the navigation signals. A sudden deviation in Doppler shift measurements may indicate an artificially generated signal from a spoofing source attempting to mislead the positioning system 100. The GNSS receiver 104 analyzes received Doppler frequencies over time to detect unnatural patterns in signal propagation. The GNSS receiver 104 may cross-reference Doppler shift observations with known satellite motion models to validate signal authenticity. The GNSS receiver 104 may implement detection thresholds to identify significant deviations beyond expected ranges. The GNSS receiver 104 may incorporate additional verification methods, comprising signal polarization analysis, to further confirm anomalies in received signals.
In an embodiment, the spoofing detection unit 110 may analyze sudden jumps in calculated location exceeding predefined kinematic movement limits as an indication of GNSS spoofing. A sudden displacement beyond expected travel speed constraints may suggest an external manipulation of navigation signals. The spoofing detection unit 110 compares time-drift anomalies in received navigation signals to identify inconsistencies caused by artificially synchronized spoofing sources. The spoofing detection unit 110 cross-checks GNSS time-stamp variations against a stored internal atomic clock reference to detect spoofing attacks. The spoofing detection unit 110 classifies detected spoofing events into at least one of signal replay, power-controlled deception, or phase-manipulated spoofing based on observed signal anomalies. The spoofing detection unit 110 may generate reports of detected spoofing attempts and store relevant data for forensic analysis. The spoofing detection unit 110 may trigger mitigation actions to counteract spoofing effects and maintain navigation integrity.
FIG. 2 illustrates a method 200 for detecting and recovering spoofing of the global navigation satellite signals, in accordance with embodiments of the present disclosure. At step 202, the GNSS receiver 104 of the user equipment 102 receives navigation signals from a plurality of space vehicles. The GNSS receiver 104 detects signals transmitted from different space vehicles and processes the received signals to extract raw navigation data. The reception process involves capturing signal timestamps, satellite ephemeris, and orbit data necessary for location determination. At step 204, the GNSS receiver 104 extracts location data from the received navigation signals. The extraction process comprises decoding transmitted data, analyzing satellite signal propagation characteristics, and applying positioning mechanisms to determine estimated coordinates. The GNSS receiver 104 derives latitude, longitude, altitude, and timestamp information based on received signals. At step 206, the reference structure 106 associated with a predetermined location transmits a location message indicative of the predetermined location. The reference structure 106 operates as a fixed landmark and continuously broadcasts a location message containing predefined coordinates through wireless communication techniques. The transmitted message serves as a ground-based validation point for location determination, assuring consistency in reference position data. At step 208, the processing unit 108 acquires the extracted location data from the user equipment 102 and the location message from the reference structure 106. The processing unit 108 establishes communication with both the user equipment 102 and the reference structure 106 to retrieve real-time navigation data. The acquired data is stored in memory and preprocessed to remove noise, correct transmission errors, and synchronize timestamps for accurate comparison. At step 210, the processing unit 108 calculates the location of the user equipment 102 based on the acquired location data and the acquired location message. The processing unit applies computational models, transformation techniques, and error correction methods to refine the calculated position. The calculated location is stored and may be further analyzed to validate accuracy. At step 212, the processing unit 108 compares the calculated location with the predetermined location of the reference structure 106 to generate a discrepancy value. The discrepancy value represents the deviation between the estimated user equipment 102 location and the reference structure coordinates. The processing unit 108 determines whether the deviation falls within acceptable thresholds or indicates potential anomalies in navigation data. At step 214, the spoofing detection unit 110 identifies a spoof indication of GNSS when the generated discrepancy value exceeds a predefined threshold. The spoofing detection unit 110 evaluates sudden jumps in location, time-drift inconsistencies, and Doppler shift variations to detect spoofing attempts. Upon detecting spoofing, the spoofing detection unit 110 logs the event and may initiate countermeasures to mitigate threats.
In an embodiment, the processing unit 108 may adjust a predefined threshold based on propagation conditions of detected global navigation satellite signals. The propagation conditions comprise factors for example ionospheric delays, tropospheric refraction, multipath interference, and signal attenuation caused by obstructions. The processing unit 108 continuously monitors variations in received signal characteristics and dynamically modifies the predefined threshold to account for environmental changes. The processing unit 108 analyzes satellite signal strength, signal-to-noise ratio, and atmospheric delay models to determine optimal threshold values. The processing unit 108 may implement statistical techniques to filter out transient anomalies which could lead to false spoofing detections. The processing unit 108 retrieves historical signal propagation data to compare current conditions with expected values, assuring an adaptive approach to threshold adjustments. The processing unit 108 may synchronize with external data sources, comprising atmospheric monitoring systems or global positioning augmentation services, to refine adjustments in real time.
In an embodiment, the processing unit 108 may generate an alert message when a spoof indication of GNSS is detected and transmits the alert message to an external monitoring system. The alert message contains details of detected spoofing attempts, comprising timestamp, affected navigation signals, discrepancy values, and classification of spoofing type. The processing unit 108 formats the alert message using standard communication protocols and transmits the message via wired or wireless communication channels. The external monitoring system may comprise centralized threat detection platforms, aviation control centers, or military surveillance networks. The processing unit 108 may encrypt the alert message to assure secure transmission and prevent unauthorized access. The processing unit 108 may prioritize the transmission of alert messages based on severity levels of detected spoofing events.
In an embodiment, the spoofing detection unit 110 may store detected spoof indications in a historical database for pattern recognition analysis. The stored data comprises signal parameters, discrepancy values, classified spoofing types, and timestamps of detected spoofing incidents. The spoofing detection unit 110 organizes the historical database for efficient retrieval and analysis of spoofing patterns. The spoofing detection unit 110 may apply statistical analysis techniques to identify recurring spoofing attempts across different time periods and geographic locations. The spoofing detection unit 110 may compare newly detected spoofing attempts with previously recorded spoof indications to determine similarities in attack characteristics. The stored historical data may be used to improve future spoof detection methods by refining threshold values and updating classification models. The spoofing detection unit 110 may establish a communication link with external security databases to exchange spoofing detection records with global monitoring agencies.
In an embodiment, the processing unit 108 may integrate GNSS signal authenticity verification with an external reference signal repository for real-time validation. The external reference signal repository contains authenticated signal samples collected from verified satellite transmissions. The processing unit 108 retrieves reference signal data from the repository and compares reference signal data with real-time received navigation signals to identify inconsistencies. The processing unit 108 may perform spectral analysis, frequency domain correlation, and statistical anomaly detection to assess authenticity of received signals. The processing unit 108 may utilize cloud-based reference databases to improve validation accuracy by accessing continuously updated signal authentication records. The processing unit 108 may implement cryptographic techniques to verify signal integrity against reference signatures stored in the repository. The processing unit 108 may transmit validation results to external monitoring entities responsible for overseeing GNSS security. The processing unit 108 may log validation outcomes for further forensic analysis of suspected spoofing incidents.
In an embodiment, the positioning system 100 may apply adaptive thresholding techniques to adjust spoof detection sensitivity based on real-time environmental conditions. The positioning system 100 evaluates environmental factors for example satellite visibility, urban infrastructure, and radio frequency interference levels to determine appropriate sensitivity settings. The positioning system 100 dynamically modifies spoof detection parameters to minimize false alarms while maintaining high detection accuracy. The positioning system 100 continuously assesses received navigation signal quality and adapts threshold values to compensate for fluctuating environmental conditions. The positioning system 100 may implement machine learning-based models trained on historical spoofing incidents to optimize adaptive threshold adjustments. The positioning system 100 may communicate with external atmospheric monitoring systems to receive updates on signal propagation conditions affecting GNSS accuracy. The positioning system 100 may periodically recalibrate detection thresholds based on long-term observations of navigation signal variations in different geographic regions.
In an embodiment, the positioning system 100 detects and recovers spoofing of global navigation satellite signals by utilizing multiple components to verify location authenticity. the user equipment 102 comprises the GNSS receiver 104 which receives navigation signals from multiple space vehicles and extracts location data. The received navigation signals are analyzed to determine satellite visibility, signal strength, and transmission timing. the reference structure 106 associated with a predetermined location transmits a location message containing fixed geographical coordinates. the processing unit 108 acquires extracted location data from the user equipment 102 and the location message from the reference structure 106. The processing unit 108 calculates a location of the user equipment 102 and compares the calculated location with the predetermined location of the reference structure 106 to generate a discrepancy value. the spoofing detection unit 110 analyzes the discrepancy value to determine whether the detected location deviations exceed a predefined threshold, indicating spoofing attempts.
In an embodiment, the user equipment 102 receives assistance data from the location server to improve accuracy of extracted location data. The location server provides real-time satellite ephemeris updates, ionospheric correction parameters, and differential positioning corrections to refine computed coordinates. The assistance data enables the user equipment 102 to mitigate environmental interferences for example signal obstructions, multipath errors, and atmospheric distortions. The user equipment 102 incorporates the assistance data into signal processing operations, reducing location errors caused by outdated or inaccurate satellite position data. The assistance data improves the reliability of navigation signals by compensating for fluctuations in space vehicle positioning and transmission characteristics. The location server dynamically updates assistance data based on GNSS signal conditions and observed anomalies in satellite transmissions.
In an embodiment, the location server generates the confidence score indicating reliability of the calculated location of the user equipment 102. The confidence score is determined based on parameters for example the number of satellites in view, signal-to-noise ratio, Doppler shift consistency, and observed discrepancies between expected and received navigation signals. The location server stores historical location data for movement pattern analysis, allowing for long-term tracking of positional trends. The stored location data is used to identify anomalies in movement behavior, which may indicate spoofing attempts or environmental interference. The location server communicates with a network for remote location determination, providing real-time validation of computed positions. The network connection allows for cross-referencing reported locations with independent geospatial databases and external monitoring systems.
In an embodiment, the processing unit 108 assesses variations in signal propagation characteristics to identify potential anomalies in location data. The processing unit 108 monitors factors for example signal delays, unexpected phase shifts, and abrupt changes in received signal strength. The processing unit 108 compares observed signal behavior with expected propagation models to determine whether inconsistencies exist. The processing unit 108 analyzes multipath interference effects by evaluating signal reflections from buildings, terrain, or other obstructions. The processing unit 108 determines whether deviations in signal parameters are caused by natural environmental factors or artificial signal manipulation. The processing unit 108 continuously adjusts detection criteria based on real-time atmospheric and geographical conditions to improve the accuracy of anomaly identification.
In an embodiment, the user equipment 102 communicates with an external client for real-time location tracking, navigation assistance, or emergency response applications. The user equipment 102 transmits computed location data to the external client using wired or wireless communication channels. The external client processes received location updates to provide navigation guidance, geofencing alerts, or emergency dispatch coordination. The communication with the external client is continuous or triggered by specific conditions, for example unexpected location deviations, movement outside predefined boundaries, or loss of signal integrity. The external client validates received location data by cross-referencing location data with historical movement patterns or external geospatial databases.
In an embodiment, the user equipment 102 estimates an uncertainty value for extracted location data based on satellite signal strength and environmental interference. The uncertainty value quantifies deviation in computed coordinates due to signal degradation, obstructions, or atmospheric disturbances. The uncertainty value is derived from factors for example satellite geometry, received signal stability, and variance in multipath effects. The user equipment 102 dynamically adjusts the uncertainty value based on real-time signal conditions, providing a measure of location reliability. The uncertainty value is used to filter out low-confidence location readings, preventing false position reporting. The user equipment 102 may transmit uncertainty values alongside computed location data to external monitoring systems for situational awareness.
In an embodiment, the user equipment 102 establishes communication with base stations or access points to obtain supplementary location information. The base stations provide additional geolocation data through network-based positioning methods for example triangulation, time-of-arrival measurements, or received signal strength analysis. The user equipment 102 integrates base station-derived positioning data with satellite-based navigation data to improve overall location accuracy. The communication with base stations is prioritized in areas with limited satellite visibility, for example urban environments, tunnels, or indoor locations. The user equipment 102 dynamically selects the most reliable data source based on signal strength, latency, and consistency of received location updates.
In an embodiment, the GNSS receiver 104 compares Doppler shift variations in received navigation signals to determine inconsistencies indicative of anomalous transmission sources. Doppler shift variations occur due to relative motion between the user equipment 102 and space vehicles transmitting navigation signals. A sudden or unexpected Doppler shift pattern suggests an artificially generated signal to mislead the positioning system 100. The GNSS receiver 104 continuously monitors Doppler variations and cross-references them with expected satellite motion models. The GNSS receiver 104 identifies spoofing events by detecting signal inconsistencies which deviate from expected Doppler shift patterns.
In an embodiment, the spoofing detection unit 110 analyzes sudden jumps in calculated location exceeding predefined kinematic movement limits as an indication of GNSS spoofing. The spoofing detection unit 110 detects unrealistic displacements which surpass physical movement constraints of the user equipment 102. The spoofing detection unit 110 compares time-drift anomalies in received navigation signals to identify inconsistencies caused by artificially synchronized spoofing sources. The spoofing detection unit 110 cross-checks GNSS timestamp variations against a stored internal atomic clock reference to detect spoofing attempts. The spoofing detection unit 110 classifies detected spoofing events into at least one of signal replay, power-controlled deception, or phase-manipulated spoofing based on observed signal anomalies.
In an embodiment, the processing unit 108 adjusts the predefined threshold based on propagation conditions of detected global navigation satellite signals. The predefined threshold serves as a reference for detecting anomalies in received navigation signals. The processing unit 108 continuously monitors signal propagation characteristics, comprising atmospheric interference, ionospheric delay, and multipath effects, to determine real-time variations in signal integrity. The processing unit 108 dynamically modifies the predefined threshold by analyzing signal-to-noise ratio, received signal power, and Doppler shift variations. The processing unit 108 may incorporate external meteorological data or space weather forecasts to anticipate signal degradation due to environmental conditions. The processing unit 108 reduces false spoofing detections by adapting detection criteria based on real-time propagation conditions. The processing unit 108 periodically recalibrates threshold values using historical signal integrity data to improve long-term accuracy in spoof detection.
In an embodiment, the processing unit 108 generates the alert message when a spoof indication of GNSS is detected and transmits the alert message to an external monitoring system. The alert message contains details of detected spoofing events, comprising timestamp, signal anomalies, discrepancy values, and classified spoofing type. The processing unit 108 formats the alert message using predefined data structures and transmits the message through secure communication channels for example encrypted wireless networks or satellite uplinks. The external monitoring system receives the alert message and processes the alert message to trigger appropriate countermeasures, comprising issuing warnings, initiating security protocols, or logging detected spoofing attempts for forensic analysis. The processing unit 108 may implement priority-based alert transmission, assuring which high-severity spoofing events receive immediate attention from external monitoring entities. The processing unit 108 may also store transmitted alert messages for future auditing and validation of spoofing incidents.
In an embodiment, the spoofing detection unit 110 stores detected spoof indications in the historical database for pattern recognition analysis. The historical database records detected spoofing attempts along with associated metadata, comprising affected satellite signals, geographic location, time of occurrence, and severity of detected anomalies. The spoofing detection unit 110 organizes stored spoof indications for efficient retrieval and analysis of recurring spoofing patterns. The spoofing detection unit 110 utilizes machine learning models or statistical techniques to analyze stored data and identify trends in spoofing behaviors. The stored spoof indications are used to refine spoof detection criteria and improve the accuracy of anomaly classification. The spoofing detection unit 110 periodically reviews stored data to identify emerging spoofing techniques and update detection parameters accordingly. The spoofing detection unit 110 may share stored spoof indications with external security agencies or GNSS monitoring centers for coordinated defense against spoofing threats.
In an embodiment, the processing unit 108 integrates GNSS signal authenticity verification with an external reference signal repository for real-time validation. The external reference signal repository maintains authenticated records of satellite signal characteristics, comprising expected transmission frequencies, modulation parameters, and time-stamped location data. The processing unit 108 retrieves reference signal data and compares reference signal data with real-time received signals to detect inconsistencies indicative of spoofing. The processing unit 108 employs frequency-domain correlation, waveform analysis, and cryptographic verification techniques to confirm signal authenticity. The processing unit 108 establishes a secure communication link with the external reference signal repository to assure continuous access to updated signal authentication records. The processing unit 108 transmits validation results to external monitoring entities for coordinated analysis and threat mitigation. The processing unit 108 logs verification outcomes to refine future spoof detection models and improve overall system reliability.
In an embodiment, the positioning system 100 applies adaptive thresholding techniques to adjust spoof detection sensitivity based on real-time environmental conditions. The positioning system 100 continuously monitors external factors for example satellite geometry, signal degradation, and interference levels to dynamically adjust spoof detection thresholds. The positioning system 100 evaluates signal anomalies in relation to environmental changes, minimizing false alarms caused by natural variations in satellite signal propagation. The positioning system 100 utilizes adaptive learning mechanisms to refine threshold parameters over time, assuring optimal spoof detection accuracy across different operational environments. The positioning system 100 periodically recalibrates detection sensitivity based on long-term observations of signal behavior in diverse geographic locations. The positioning system 100 may communicate with external atmospheric monitoring systems or global positioning augmentation services to receive environmental data which influences spoof detection adjustments. The positioning system 100 applies data-driven techniques to optimize spoof detection sensitivity while maintaining reliable navigation performance.
FIG. 3 illustrates a state diagram of the positioning system 100 for detecting and recovering spoofing of global navigation satellite signals, in accordance with embodiments of the present disclosure. The process begins with receiving GNSS signals, followed by extracting location data. A reference structure 106 then transmits a location message containing a predetermined position. A processing unit 108 acquires the extracted location data from a user equipment 102 and the reference message from the reference structure 106. The processing unit 108 calculates the location of the user equipment 102 and compares with the predetermined location of the reference structure 106, generating a discrepancy value. A spoofing detection unit 110 evaluates whether the discrepancy value exceeds a predefined threshold. If the value is below the threshold, the location is considered valid. If the value exceeds the threshold, a spoofing event is identified, triggering an alert or countermeasure to mitigate threats and maintain positioning accuracy.
FIG. 4 illustrates a schematic diagram of signal reception and spoofing detection, in accordance with the embodiments of the present disclosure. The process begins with receiving GNSS signals, followed by extracting location data. A reference structure 106 then transmits a location message containing a predetermined position. A processing unit 108 acquires the extracted location data from a user equipment 102 and the reference message from the reference structure 106. The processing unit 108 calculates the location of the user equipment 102 and compares with the predetermined location of the reference structure 106, generating a discrepancy value. A spoofing detection unit 110 evaluates whether the discrepancy value exceeds a predefined threshold. If the value is below the threshold, the location is considered valid. If the value exceeds the threshold, a spoofing event is identified, triggering an alert or countermeasure to mitigate threats and maintain positioning accuracy.
In the description of the present invention, it is also to be noted that, unless otherwise explicitly specified or limited, the terms “disposed,” “mounted,” and “connected” are to be construed broadly, and may for example be fixedly connected, detachably connected, or integrally connected, either mechanically or electrically. They may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Modifications to embodiments and combination of different embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions for example “comprising”, “comprising”, “incorporating”, “have”, “is” used to describe and claim the present disclosure are intended to be construed in a non- exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.
Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the present disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.
,CLAIMS:WE CLAIM:
1. A positioning system 100 to detect and recover spoofing of the global navigation satellite signals, comprising:
a user equipment 102 comprising a global navigation satellite system (GNSS) receiver 104, wherein the GNSS receiver 104 is configured to receive the navigation signals from a plurality of space vehicles and extract location data based on the received navigation signals;
a reference structure 106 associated with a predetermined location, wherein the reference structure 106 is configured to transmit a location message indicative of the predetermined location;
a processing unit 108 communicatively linked to the user equipment 102 and the reference structure 106, wherein the processing unit 108 is configured to:
acquire the extracted location data and the location message from the user equipment 102 and the reference structure 106, respectively;
calculate a location of the user equipment 102 based on the acquired location data and the acquired location message; and
compare the calculated location with the predetermined location of the reference structure 106 to generate a discrepancy value;
a spoofing detection unit 110 operatively coupled to the processing unit 108, wherein the spoofing detection unit 110 is configured to identify a spoof indication of GNSS when the generated discrepancy value exceeds a predefined threshold.
2. The positioning system 100 of claim 1, wherein the user equipment 102 is configured to receive assistance data from a location server to improve accuracy of the extracted location data.
3. The positioning system 100 of claim 2, wherein the location server is configured to:
generate a confidence score indicating reliability of the calculated location of the user equipment 102;
store historical location data for movement pattern analysis; and
communicate with a network for remote location determination.
4. The positioning system 100 of claim 1, wherein the processing unit 108 is configured to assess the variations in the signal propagation characteristics to identify the potential anomalies in location data.
5. The positioning system 100 of claim 1, wherein the user equipment 102 is configured to communicate with an external client for real-time location tracking, navigation assistance, or the emergency response applications.
6. The positioning system 100 of claim 1, wherein the user equipment 102 is configured to estimate an uncertainty value for the extracted location data based on a satellite signal strength and an environmental interference.
7. The positioning system 100 of claim 1, wherein the user equipment 102 is configured to establish communication with the base stations or the access points to obtain supplementary location information.
8. The positioning system 100 of claim 1, wherein the GNSS receiver 104 is configured to compare the Doppler shift variations in the received navigation signals to determine the inconsistencies indicative of the anomalous transmission sources.
9. The positioning system 100 of claim 1, wherein the spoofing detection unit 110 is configured to:
Analyze the sudden jumps in calculated location exceeding the predefined kinematic movement limits as an indication of GNSS spoofing;
compare the time-drift anomalies in the received navigation signals to identify the inconsistencies caused by the artificially synchronized spoofing sources;
cross-check the GNSS time-stamp variations against a stored internal atomic clock reference to detect the spoofing attacks; and
classify the detected spoofing events into at least one of a signal replay, a power-controlled deception, or a phase-manipulated spoofing based on the observed signal anomalies.
10. A method 200 for detecting and recovering spoofing of the global navigation satellite signals, the method 200 comprising:
receiving, by a global navigation satellite system (GNSS) receiver 104 of a user equipment 102, the navigation signals from a plurality of space vehicles;
extracting, by the GNSS receiver 104, location data from the received navigation signals;
transmitting, by a reference structure 106 associated with a predetermined location, a location message indicative of the predetermined location;
acquiring, by a processing unit 108, the extracted location data from the user equipment 102 and the location message from the reference structure 106;
calculating, by the processing unit 108, a location of the user equipment 102 based on the acquired location data and the acquired location message;
comparing, by the processing unit 108, the calculated location with the predetermined location of the reference structure 106 to generate a discrepancy value; and
identifying, by a spoofing detection unit 110, a spoof indication of GNSS when the generated discrepancy value exceeds a predefined threshold.
11. The method 200 of claim 10, wherein the processing unit 108 is configured to adjust the predefined threshold based on the propagation conditions of the detected global navigation satellite signals.
12. The method 200 of claim 10, wherein the processing unit 108 is configured to generate an alert message when the spoof indication of GNSS is detected, wherein the alert message is transmitted to an external monitoring system.
13. The method 200 of claim 10, wherein the spoofing detection unit 110 is configured to store the detected spoof indications in a historical database for pattern recognition analysis.
14. The method 200 of claim 10, wherein the processing unit 108 is configured to integrate GNSS signal authenticity verification with an external reference signal repository for real-time validation.
15. The method 200 of claim 10, wherein the positioning system 100 is configured to apply adaptive the thresholding techniques to adjust spoof detection sensitivity based on the real-time environmental conditions.