Honeywell International Inc.

Honeywell Aerospace Sas

Martin Orejas

Jussi Raasakka

Jakub Skalicky

Ondrej Kutik

Zdenek Kana

Jindrich Dunik

Lucas Almeida Cypriano

Tomas Hynek

Michal Zaruba

Matej Kucera

Michal Pfleger

Jolana Kristufkova Dvorska

A method comprises computing position information from a global navigation satellite system (GNSS); computing an altitude measurement based on retrieved information from a vertical position sensor; determining a vertical protection level (VPL) associated with the position information; splitting the VPL into an upward VPL component and a downward VPL component; determining a vertical alert limit (VAL) associated with the altitude measurement; and splitting the VAL into an upward VAL component and a downward VAL component. The method optimizes an integrity budget allocation between the upward and downward VPL components. The method then recomputes the upward and downward VPL components given the optimized integrity budget allocation.

Split vertical advanced receiver autonomous integrity monitoring

Systems and methods for handling ARAIM terrain database induced errors are described herein. In certain embodiments, a method includes computing position information from a global navigation satellite system. The method further includes computing altitude based on retrieved information from a vertical position sensor and a terrain database. Additionally, the method includes computing a horizontal protection level associated with the position information. Also, the method includes estimating an error for a terrain database based on the altitude, position information, and the horizontal protection level. Moreover, the method includes calculating a new protection level based on the position information and the altitude accounting for the estimated error for the terrain database.

Handling of ARAIM terrain database induced errors

Systems and methods for reducing bias impact on GNSS integrity are described herein. In certain embodiments, a method includes determining a phase of travel of a vehicle. The method also includes determining a probability of hazardously misleading information (PHMI) for the corresponding phase of travel. Further, the method includes determining a protection level (PL) using based on the PHMI, wherein the PL is calculated based on a standard deviation of position error plus a standard deviation of bias along an axis of interest. Additionally, the method includes comparing the protection level against an alert limit.

Reducing bias impact on GNSS integrity

A baseband tracking channel in a GNSS receiver is provided. The baseband tracking channel comprises: a code generator to generate a local signal correlating with an incoming signal received by the GNSS receiver; a multiplier that multiplies the local signal with a baseband signal corresponding to an incoming signal received by the GNSS receiver to generate a code removed signal; a prompt correlator including at least one integration register that integrates samples of the code removed signal corresponding to a first portion of each pseudorandom noise code chip of the code removed signal to provide a first integration register output, and integrates samples corresponding to a second portion of each PRN code chip to provide a second integration register output; and a side peak tracking detection module that generates information indicating when side peak tracking is occurring based on the first integration register output and the second integration register output.

Side peak tracking detection

A method of global navigation satellite system (GNSS) acquisition comprises: computing a line of sight (LOS) angle between a LOS vector of a first satellite and a LOS vector of a second satellite, wherein each LOS vector is the LOS vector between a receiver and the respective satellite; computing a maximum Doppler difference, wherein the maximum Doppler difference is computed between the first satellite and the second satellite based on the LOS angle and a maximum velocity vector attainable by the receiver, wherein Doppler is induced at least by movement of the receiver; determining a final frequency search range based on the maximum Doppler difference computed between the first satellite and the second satellite, wherein the frequency search range includes a center frequency equal to the first frequency at which the first satellite is found; acquiring a GNSS signal from the second satellite at a second frequency.

Reducing frequency search space for global navigation satellite system acquistion

A GNSS receiver comprising at least one processing device configured to, in at least one first process: group satellites into subsets for a first distribution, each satellite included in one subset, each subset includes at least one satellite and less than all satellites, at least one subset includes more than one satellite; store the first distribution in memory as primary distribution; calculate a protection level based on navigation sub-solutions calculated using the first distribution; determine whether a new distribution of satellites is needed; when new distribution is not needed, the processing device configured to recalculate the protection level based on second navigation sub-solutions calculated using the first distribution; when new distribution is needed, the processing device configured to: group satellites into subsets for a second distribution; store the second distribution in memory as the primary distribution; recalculate the protection level based on third navigation sub-solutions calculated using the second distribution.

ARAIM clustering distribution improvement

A global navigation satellite system (GNSS) receiver including a processing device configured to: group GNSS satellites in view of the GNSS receiver into subsets based on relative geometries of the GNSS satellites relative to the GNSS receiver, wherein a GNSS satellite of the GNSS satellites is included in at most one subset of the subsets, wherein each subset of the subsets includes at least one GNSS satellite of the GNSS satellites and less than all GNSS satellites of the GNSS satellites, and wherein at least one subset includes more than one GNSS satellite; calculate a plurality of navigation sub-solutions based on data received at the GNSS receiver from the GNSS satellites using at least one GNSS antenna, wherein each navigation sub-solution of the navigation sub-solutions is calculated with at least one different subset of the subsets excluded; and calculate a protection level based on the navigation sub-solutions.

Smart satellite distribution into ARAIM clusters for use in monitoring integrity of computed navigation solutions

A Global Navigation Satellite System receiver comprising at least one processor is provided. The processor is configured to: determine a weighted false alarm probability allocation for at least one sub-solution in a solution separation based integrity monitoring module, wherein the weighted false alarm probability allocation is based on pre-determined values for missed detection probability and fault probability for the sub-solution, wherein the at least one sub-solution is created by excluding a set of potentially faulty satellites from a full solution, wherein a fault mode occurs when there is a faulty satellite in the excluded set of potentially faulty satellite, wherein the at least one sub-solution's missed detection probability is probability that detection of associated fault mode occurrence in a sub-solution was missed, and wherein the at least one sub-solution's fault probability is probability that the fault mode occurs; compute a weighted protection level based on the weighted false alarm probability.

False alarm distribution in advanced receiver autonomous integrity monitoring

An efficient covariance matrix computation method is disclosed in connection with certain GNSS applications, including Advanced Receiver Autonomous Integrity Monitoring (ARAIM) and geometry screening. The system and method of the present application enable computation of multiple covariance matrices with substantially greater efficiency than previous approaches, including the rank-one update formula. For example, the system and method of the present application advantageously involves substantially fewer and simpler arithmetic operations than previous approaches. In addition, unlike the rank-one update formula, the system and method of the present application can be used to compute the subsolution in which all the satellites of a given constellation are removed.

Efficient covariance matrix update

A global navigation satellite system (GNSS) receiver includes: at least one radio frequency (RF) front end configured to receive a GNSS signal from a single GNSS antenna and to digitize the GNSS signal into a digitized GNSS signal; at least one processor configured to: calculate weight to be applied to a sample of a block of samples of the digitized GNSS signal; apply the weight to at least one sample of the block of samples of the digitized GNSS signal to create a weighted GNSS signal; and perform signal processing on the weighted GNSS signal.

Weighting algorithm for signal processing

A method of advanced receiver autonomous integrity monitoring of a navigation system is discussed and two modifications facilitating its implementation in a hybrid navigation system are disclosed. In the first approach, relations describing the effect of unmodeled biases in pseudo-measurement on the Kalman filter state estimate are analytically derived and their incorporation into the integrity monitoring algorithm is described. The method comprises receiving a plurality of signals transmitted from space-based satellites, determining a position full-solution and sub-solutions, specifying a pseudorange bias, computing a transformation matrix for the full-solution and all sub-solutions using a Kalman filter, computing a bias effect on an error of filtered state vectors of all sub-solutions, and adding the effect to computed vertical and horizontal protection levels. In the second approach, a modification for computationally effective calculation of the protection levels of hybrid navigation systems based on both integrity and non-integrity assured pseudorange error descriptions is disclosed.

Selected aspects of advanced receiver autonomous integrity monitoring application to kalman filter based navigation filter

Embodiments for satellite subset selection for use in monitoring the integrity of computed navigation solutions are disclosed. In one embodiment, a Global Navigation Satellite System (GNSS) receiver comprises: a processing device configured to: group a plurality of satellites in view of the GNSS receiver into a plurality of subsets, wherein a satellite of the plurality of satellites is included in at most one subset of the plurality of subsets, wherein each subset of the plurality of subsets includes at least one satellite of the plurality of satellites and less than all satellites of the plurality of satellites, and wherein at least one subset includes more than one satellite; calculate a plurality of navigation sub-solutions, wherein each navigation sub-solution of the plurality of navigation sub-solutions is calculated with at least one different subset of the plurality of subsets excluded; and calculate a protection level.

Satellite subset selection for use in monitoring the integrity of computed navigation solutions

A method comprises receiving a plurality of signals from a plurality of space-based satellites, wherein the plurality of space-based satellites comprises at least one space-based satellite from each of a plurality of Navigation Satellite System (NSS) constellations. The method also comprises determining, in a first domain, a first plurality of sub-solutions based on a respective sub-set of the plurality of signals, each respective sub-set in the first domain chosen according to a characteristic defining the first domain; and determining, in a second domain, a second plurality of sub-solutions based on a respective sub-set of the plurality of signals, each respective sub-set in the second domain chosen according to a characteristic defining the second domain. The method further comprises determining if an error is present in the navigation system based on the first plurality of sub-solutions and on the second plurality of sub-solutions.

Architectures for high integrity multi-constellation solution separation

In one embodiment, a method for selecting a sub-set of satellites from a set of N satellites is provided. The method includes recursively evaluating each sub-set of N&#x2212;P satellites of a set of N satellites. If only one sub-set satisfies one or more first criterion, then the one sub-set that satisfies the one or more first criterions is selected. If, however, more than one sub-set satisfies the one or more first criterion, then the sub-sets that satisfy the one or more first criterion are evaluated with respect to one or more second criterion and the one sub-set that optimizes the one or more second criterion is selected. Once the selected set of N satellites is equal to the number of satellites from which a receiver is configured to calculate a navigation solution, then that selected set of N satellites is used to calculate a navigation solution.

Multiple-criterion based global navigation satellite sub-set recursive selection

A global navigation satellite system (GNSS) receiver includes a processor to determine whether a first satellite is in view of GNSS receiver; whether a second satellite is in view of GNSS receiver when first satellite is in view of GNSS receiver; and whether a third satellite is in view of GNSS receiver when first satellite is not in view of GNSS receiver. Second satellite was previously determined more likely to be in view when first satellite is in view based on a first average distance between first satellite and second satellite based on a first orbit of first satellite and a second orbit of second satellite. Third satellite was previously determined more likely to be in view when first satellite is not in view based on a second average distance between first satellite and third satellite based on first orbit of first satellite and a third orbit of third satellite.

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Brno, Czechia

Martin Orejas