BACKGROUND

In selected differential Global Positioning System (GPS) based applications, such as the Joint Precision Approach and Landing System (JPALS), relative navigation functions must meet requirements for high accuracy, high integrity, and high availability. To ensure sub-meter accuracy (e.g., within 20 cm), navigation solutions may be formed using GPS carrier phase measurements. GPS carrier phase integer ambiguities may then be fixed via a Real Time Kinematic (RTK) technique such as the Least-squares AMBiguity Decorrelation Algorithm (LAMBDA) or an integer bootstrapping algorithm. To ensure high integrity, protection levels can be computed to bound errors in the computed navigation solution to a desired degree of confidence. Protection levels depend, among other factors, on the success rate of the carrier phase integer ambiguity fixing process. Generally, if the probability of correct fix (PCF) is sufficiently high, both accuracy and protection levels may be improved with fixed integer ambiguities (as opposed to float integer ambiguities). If the PCF is not high enough, however, improved protection levels may not result from estimated fixed integer ambiguities (relative to estimated float integer ambiguities), even though nominal accuracy may improve. Consequently, both availability and accuracy may suffer, as a fixed solution may not be available after protection levels exceed alert limits.

One technique for maintaining the PCF (i.e., ensuring a reasonably high success rate) while maintaining high accuracy may involve partial ambiguity fixing: fixing only a subset of integer ambiguities that can be estimated with higher confidence while using float integer ambiguity estimates for the remainder, trading accuracy for lower protection levels. However, in the original carrier phase measurement ambiguity domain, using integer bootstrapping alone may lead to lower PCF and higher protection levels. Use of LAMBDA algorithms with integer bootstrapping to decorrelate ambiguities prior to fixing may increase the PCF and lower protection levels; however, the use of LAMBDA may complicate partial fixing.

SUMMARY

A system for determining high-integrity navigation solutions is disclosed. In embodiments, the system includes one or more processors configured for receiving multiple sets satellite-based navigational data from diverse sources using common navigational satellites, e.g., Global Positioning System (GPS) carrier phase measurements from a GPS receiver on board the aircraft in which the system is embodied as well as GPS data from another proximate vehicle (e.g., a carrier on which the aircraft is approaching to land upon). Based on the received GPS data, the system generates a set of GPS floating-point ambiguities. By decorrelating the floating-point ambiguities according to Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) algorithms, the system generates a baseline navigational solution in the LAMBDA domain. From this baseline solution, the system selects decorrelated floating-point ambiguities to be fixed, one at a time. The system determines a protection level associated with a partial almost-fix solution (PAFS) based on the set of floating-point ambiguities and a Probability of Almost Fix (PAF) based on the probability that the PAFS is bounded by the protection level. The system fixes a first decorrelated floating-point ambiguity in the LAMBDA domain and updates the PAFS by substituting the floating-point ambiguity with the corresponding fixed ambiguity. While the PAF remains above a predetermined threshold and the protection level remains below a predetermined alert level, the system selects additional decorrelated floating-point ambiguities to fix and continues to update the PAFS by substituting the appropriate floating-point ambiguities with the corresponding fixed ambiguities. Should the PAF reach the threshold level, or the protection level reach the alert level, the system reverts to and outputs the most recently updated PAFS, replacing the most recently substituted fixed ambiguity with its corresponding floating-point ambiguity from the original set.

A Joint Precision and Approach Landing System (JPALS) is also disclosed. The JPALS is embodied aboard an aircraft and includes a GPS or similar satellite-based navigational receiver for determining position data based on GPS carrier phase signals received from navigational satellites. In embodiments, the JPALS includes processors for receiving the GPS signals used by the navigational receiver to determine ownship position as well as additional GPS carrier phase data from other sources (e.g., a carrier or other vehicle proximate to the aircraft, and upon which the aircraft is approaching to land). Based on the received GPS data, the JPALS generates a set of GPS floating-point ambiguities. By decorrelating the floating-point ambiguities according to LAMBDA algorithms, the JPALS generates a baseline navigational solution in the LAMBDA domain. From this baseline solution, the JPALS selects decorrelated floating-point ambiguities to be fixed, one at a time. The JPALS determines a protection level associated with a partial almost-fix solution (PAFS) based on the set of floating-point ambiguities and a Probability of Almost Fix (PAF) based on the probability that the PAFS is bounded by the protection level. The JPALS fixes a first decorrelated floating-point ambiguity in the LAMBDA domain and updates the PAFS by substituting the floating-point ambiguity of the original set with the corresponding fixed ambiguity. While the PAF remains above a predetermined threshold and the protection level remains below a predetermined alert level, the JPALS selects additional decorrelated floating-point ambiguities to fix and continues to update the PAFS by substituting the appropriate floating-point ambiguities with the corresponding fixed ambiguities. Should the PAF reach the threshold level, or the protection level reach the alert level, the JPALS reverts to and outputs the most recently updated PAFS, replacing the most recently substituted fixed ambiguity with its corresponding floating-point ambiguity from the original set.

A method for determining high-integrity navigation solutions is also disclosed. In embodiments, the method includes receiving, via a processor, satellite-based navigation data from at least two satellite-based navigation sources (e.g., an aircraft within which the processor is embodied as well as a proximate aircraft or other vehicle) associated with one or more common navigation satellites. The method includes generating, via the processor, a set of floating-point ambiguities based on the received satellite-based navigation data. The method includes generating, via the processor, a baseline navigational solution in the LAMBDA domain by decorrelating each of the set of floating-point ambiguities in the LAMBDA domain. The method includes selecting, via the processor, a first decorrelated floating-point ambiguity of the baseline solution to be fixed. The method includes determining, via the processor, a protection level associated with a partial almost-fix solution (PAFS). The method includes determining, via the processor, a Probability of Almost Fix (PAF) based on a probability that the partial almost-fix solution is bounded by the protection level. The method includes fixing the first selected decorrelated floating-point ambiguity of the baseline solution. The method includes generating the partial almost-fix solution by substituting with the fixed ambiguity, in the original set of floating-point ambiguities, the floating-point ambiguity corresponding to the most recently fixed selected decorrelated floating-point ambiguity of the baseline solution. The method includes, while the PAF remains above a threshold level and the protection level remains below an alert level, selecting from the baseline solution additional decorrelated floating-point ambiguities to be fixed and fixing the selected decorrelated floating-point ambiguities in the LAMBDA domain. The method includes updating the partial almost-fix solution by substituting the floating-point ambiguities corresponding to the selected decorrelated floating-point ambiguities with the corresponding fixed ambiguities. Should the PAF reach the threshold or the protection level reach the alert level, the method includes reverting to the last recently updated partial almost-fix solution by replacing the most recently substituted fixed ambiguity with its corresponding floating-point ambiguity.

This Summary is provided solely as an introduction to subject matter that is fully described in the Detailed Description and Drawings. The Summary should not be considered to describe essential features nor be used to determine the scope of the Claims. Moreover, it is to be understood that both the foregoing Summary and the following Detailed Description are example and explanatory only and are not necessarily restrictive of the subject matter claimed.

