A method for reduced-outlier satellite positioning includes receiving a set of satellite positioning observations at a receiver; generating a first receiver position estimate; generating a set of posterior observation residual values from the set of satellite positioning observations and the first receiver position estimate; based on the set of posterior observation residual values, identifying a subset of the satellite positioning observations as statistical outliers; and after mitigating an effect of the statistical outliers, generating a second receiver position estimate having higher accuracy than the first receiver position estimate.

A method for reduced-outlier satellite positioning includes receiving a set of satellite positioning observations at a receiver; generating a first receiver position estimate; generating a set of posterior observation residual values from the set of satellite positioning observations and the first receiver position estimate; based on the set of posterior observation residual values, identifying a subset of the satellite positioning observations as statistical outliers; and after mitigating an effect of the statistical outliers, generating a second receiver position estimate having higher accuracy than the first receiver position estimate.

An authentication system that performs authentication of first location information collected from an apparatus includes an acquisition section configured to acquire one or more pieces of authentication information to be used for the authentication, and an authentication section that determines, using the one or more pieces of authentication information acquired by the acquisition section, whether the first location information is counterfeited, by an authentication method corresponding to each of the one or more pieces of authentication information to authenticate the first location information.

An authentication system that performs authentication of first location information collected from an apparatus includes an acquisition section configured to acquire one or more pieces of authentication information to be used for the authentication, and an authentication section that determines, using the one or more pieces of authentication information acquired by the acquisition section, whether the first location information is counterfeited, by an authentication method corresponding to each of the one or more pieces of authentication information to authenticate the first location information.

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.

Some embodiments of the invention relate to methods carried out by an NSS receiver and/or a processing entity capable of receiving data therefrom, for estimating parameters derived from NSS signals and detecting outliers in NSS observables. Input data comprising signals observed by the receiver is received. An estimator is operated, which uses state variables and computes the values thereof based on the input data. An outlier detection procedure comprises: computing a first statistic based on data outputted from the estimator and associated with a set of observables; identifying an observable candidate for removal; computing a second statistic based on the data outputted from the estimator from which the data associated with the identified observable is removed; and determining whether the ratio of the first to the second statistic exceeds a threshold and, if so, removing the identified observable, having the estimator recompute its state variables and performing the outlier detection procedure again.

Some embodiments of the invention relate to methods carried out by an NSS receiver and/or a processing entity capable of receiving data therefrom, for estimating parameters derived from NSS signals and detecting outliers in NSS observables. Input data comprising signals observed by the receiver is received. An estimator is operated, which uses state variables and computes the values thereof based on the input data. An outlier detection procedure comprises: computing a first statistic based on data outputted from the estimator and associated with a set of observables; identifying an observable candidate for removal; computing a second statistic based on the data outputted from the estimator from which the data associated with the identified observable is removed; and determining whether the ratio of the first to the second statistic exceeds a threshold and, if so, removing the identified observable, having the estimator recompute its state variables and performing the outlier detection procedure again.

A system and for determining precision navigation solutions decorrelates GPS carrier-phase ambiguities derived from multiple-source GPS information via Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) algorithms. The set of decorrelated floating-point ambiguities is used to compute protection levels and the probability of almost fix (PAF), or the probability that the partial almost-fix solution corresponding to the decorrelated ambiguities is within the region of correctly-fixed or low-error almost-fixed ambiguities. While the PAF remains below threshold and the protection levels remain below alert levels, the optimal navigation solution (floating-point, partial almost-fix, or fully fixed) is generated by fixing the decorrelated ambiguities are one at a time in the LAMBDA domain and replacing the appropriate carrier-phase ambiguities with the corresponding fixed ambiguities, reverting to the last solution if PAF reaches the threshold or if protection levels reach the alert levels.

A method comprises receiving an ILS transmission signal in an onboard ILS receiver during an aircraft approach, and receiving a GNSS position signal in an onboard GNSS augmentation system receiver during the approach. The method determines a first set of flight path deviations based on the ILS transmission signal, and a second set of flight path deviations based on the GNSS position signal. The first set of flight path deviations are sent to a first complementary filter, which outputs a first filtered deviations signal. The second set of flight path deviations is sent to a second complementary filter, which outputs a second filtered deviations signal. A scale factor is applied to the first filtered deviations signal or the second filtered deviations signal, such that the filtered deviations signals are normalized to the same scale. The method combines the normalized filtered deviations signals to produce a hybrid signal for further processing.