A system for navigating a mobile object receives satellite navigation signals from a plurality of satellites. Using one or more of the satellite navigation signals from the plurality of satellites, for each respective channel of a plurality of channels, the system generates an estimate of clock error of a clock of the mobile object using a first error correction stage and generates an estimate of a respective carrier tracking error for the respective channel using a second error correction stage that is distinct from the first error correction stage. In accordance with the estimate of the clock error and the estimate of the respective carrier tracking error for each of the plurality of channels, the system computes position and velocity estimates for the mobile object. The system performs a navigation function for the mobile object in accordance with the computed position and velocity estimates for the mobile object.

A system for navigating a mobile object receives satellite navigation signals from a plurality of satellites. Using one or more of the satellite navigation signals from the plurality of satellites, for each respective channel of a plurality of channels, the system generates an estimate of clock error of a clock of the mobile object using a first error correction stage and generates an estimate of a respective carrier tracking error for the respective channel using a second error correction stage that is distinct from the first error correction stage. In accordance with the estimate of the clock error and the estimate of the respective carrier tracking error for each of the plurality of channels, the system computes position and velocity estimates for the mobile object. The system performs a navigation function for the mobile object in accordance with the computed position and velocity estimates for the mobile object.

A method and a function for checking the integrity of the processing of a radionavigation signal emitted by a satellite, the signal being received by a receiver comprising reception means and processing means, the processing means comprising a linear anti-interference filter, the integrity checking method comprising at least a first phase of detection of a risk of false lock-on comprising the following steps: a step of recovery of a nominal theoretical self-correlation function of the received signal not processed by the linear anti-interference filter; a step of determination of a mean theoretical self-correlation function of the signal received and processed by the linear anti-interference filter over a defined integration period; a step of determination of the number of local maxima of the modulus or of the modulus squared of the mean theoretical self-correlation function, a risk of false lock-on being detected if the number of local maxima is greater than or equal to two.

A Global Navigation Satellite System (GNSS) receiver for performing GNSS outlier detection and rejection is provided. When the GNSS receiver receives GNSS signals from satellites in the GNSS, the GNSS receiver processes the GNSS signals to perform positioning. Then, the GNSS receiver sequentially performs a Doppler-pseudorange comparison, a Random Sampling Consensus (RANSAC) check for selected subsets of the satellites, and a history-based check for the satellites to determine a status of each satellites as an outlier or an inlier. Specifically, in the RANSAC check, the subsets of the satellites are selected using results of the Doppler-pseudorange comparison as inputs to filter the satellites, thus reducing the number of subsets needed for computation in the RANSAC check. The status of the satellites are recorded for the history-based check, which further exploits the correlations of outliers across time.

A Global Navigation Satellite System (GNSS) receiver for performing GNSS outlier detection and rejection is provided. When the GNSS receiver receives GNSS signals from satellites in the GNSS, the GNSS receiver processes the GNSS signals to perform positioning. Then, the GNSS receiver sequentially performs a Doppler-pseudorange comparison, a Random Sampling Consensus (RANSAC) check for selected subsets of the satellites, and a history-based check for the satellites to determine a status of each satellites as an outlier or an inlier. Specifically, in the RANSAC check, the subsets of the satellites are selected using results of the Doppler-pseudorange comparison as inputs to filter the satellites, thus reducing the number of subsets needed for computation in the RANSAC check. The status of the satellites are recorded for the history-based check, which further exploits the correlations of outliers across time.

A method for preprocessing data for device operations can include preprocessing measurement data using a machine learning technique, determining, by a Kalman filter and based on (1) the preprocessed measurement data or the measurement data and (2) prediction data from a prediction model predicting a measurement associated with the measurement data, corrected measurement data, and providing the corrected measurement data based on the predicted measurement and the preprocessed measurement data.

A method for preprocessing data for device operations can include preprocessing measurement data using a machine learning technique, determining, by a Kalman filter and based on (1) the preprocessed measurement data or the measurement data and (2) prediction data from a prediction model predicting a measurement associated with the measurement data, corrected measurement data, and providing the corrected measurement data based on the predicted measurement and the preprocessed measurement data.

A multiple faulty global navigation satellite signal detecting system is provided. The system includes at least one pair of spaced antennas, at least one aiding source and processor. The at least one pair of spaced antennas are configured to receive satellite signals from a plurality of satellites. The at least one aiding source is used to generate aiding source position estimate signals. The processor is in communication with each antenna and the at least one aiding source. The processor is configured to determine signals blocks. The signal blocks being a collection of subsets of the determined difference signals and a covariance matrix for the difference signals. The processor further configured to generate a union of good signals from all the good blocks and a complementary set of bad signals.

Signal, data transmission, and/or encryption units generating a cryptographic code using a cryptographic key before writing to a pseudorandom noise buffer memory. The PRN code generator comprises a first processor generating a PRN code from initial data using a cryptographic key. A second processor generates sections of the PRN code for integrity check purposes through computation using the same cryptographic key and initial data. Within the PRN code generator and before temporary storage of the PRN code in the buffer memory, there is a comparison device for comparing at least one duplicated section of the PRN code sequence cryptographically generated by the first processor with the section computed by the second processor. A blocking, stop and/or alarm function is activated in the comparison device and triggered on the basis of a predefined degree of matching between the section obtained through duplication and the computed section.

Existing networks of precisely surveyed GNSS receivers that are used for dGNSS or RTK positioning techniques can be used to measure GNSS time across a territory or region such as a country. The measured GNSS time base signals from each receiver are then fed back to a collating service, similar to the existing dGNSS/RTK systems, which also receives an accurate time base signal from a trusted third-party time base supplier which maintains a trusted time base. The collating service then compares the GNSS time signals from the network of GNSS receivers with the trusted time base and determines whether the GNSS time signals are accurate when compared to the trusted time base, and if they are not accurate, calculates the error. The collating service may provide the calculated error to users and the necessary correction that needs to be applied to measured GNSS time to obtain accurate UTC time.