Integrity risk is a measure of localization safety that accounts for the presence of undetected sensor faults. The metric has been used for decades in aviation and has recently been applied to terrestrial robots operating in life-critical missions. For ground vehicles, integrity risk can be quantified for systems using lidar measurements, where two specific fault types have been identified: miss-association and unmapped association. While miss-association faults, which occur when a correctly extracted feature is associated to the wrong landmark, have been well-studied, the probability of an unmapped association fault, where an incorrectly extracted feature is associated to a landmark, is not well-understood. Namely, previous research has never quantified this value and instead relies on an assumed value, one whose value has not been properly justified. This work is the first to provide a methodology that estimates the risk of unmapped association for each mapped landmark; the paper demonstrates the effect of this probability for both the chi-squared and fixed-lag smoothing methods for integrity monitoring. Data collected in downtown Chicago, IL USA was used to test the impact of unmapped association faults on localization safety. The results indicate that using the previously assumed value is reasonable in many situations, but that applications with strict safety requirements should incorporate the method described here to properly account for unmapped association faults.

Global Navigation Satellite System (GNSS) reflectometry leverages signals of opportunity to remotely sense the Earth's surface for a variety of science investigations. However, ionospheric refraction affects GNSS reflections detected at low Earth orbit (LEO). While multifrequency GNSS enables the elimination of most of the ionospheric error, single-frequency missions are still susceptible to this ranging delay. Motivated by the planned launch of Cyclone GNSS (CYGNSS) in 2016, a single-frequency reflectometry mission, this letter presents a simulation of the relative ionospheric delay that will shift the Delay-Doppler Map (DDM) data product. A mathematical model is presented that defines and characterizes signal propagation delay in the DDM. The model differentiates direct and reflected signals as a sum of path lengths, atmospheric refraction effects, and noise. We simulate representative ionospheric delays from the model associated with the direct and reflected ray paths as a function of satellite elevation angle, latitude, and solar activity. Simulation using the International Reference Ionosphere 2007 shows that differential ionospheric content is inversely proportional to satellite elevation angle and that low latitudes present larger ionospheric impacts on the reflected signals. Finally, high solar activity conditions lift the ionospheric density profile to and possibly above the CYGNSS orbit altitude of 500 km. The ionospheric delay will not generally affect the estimation of wind speed but may affect the CYGNSS signal acquisition and open loop tracking process. Implications of the ionospheric delay in other GNSS reflectometry applications are also discussed.

The United States Navy seeks the capability to land manned and unmanned aerial vehicles autonomously on an aircraft carrier using GPS. To deliver this capability, the Navy is developing a navigation system called the Sea-Based Joint Precision Approach and Landing System (JPALS). Because standard GPS is not sufficiently precise to land aircraft on a shortened, constantly moving runway, Sea-Based JPALS leverages dual-frequency, carrier-phase differential GPS navigation. Carrier phase measurements, derived from the sinusoidal waveforms underlying the GPS signal, are very precise but not necessarily accurate unless the user resolves the ambiguity associated with the sinusoid's periodicity. Ensuring the validity of ambiguity resolution is the central challenge for the high-integrity, safety-critical JPALS application. Based on a multi-year, multi-institution collaborative study, this paper proposes a navigation and monitoring architecture designed to meet the guidance quality challenge posed by Sea-Based JPALS. In particular, we propose a two-stage navigation algorithm that meets the aggressive integrity-risk requirement for Sea-Based JPALS by first filtering a combination of GPS observables and subsequently exploiting those observables to resolve the carrier ambiguity. Because JPALS-equipped aircraft may encounter jamming, we also discuss interference mitigation technologies, such as inertial fusion and array antennas, which, with appropriate algorithmic modifications, can ensure integrity under Radio Frequency Interference (RFI) conditions. Lastly, we recommend a fault monitoring strategy tailored to the two-stage navigation algorithm. Monitoring will detect and isolate rare anomalies such as ionosphere storms or satellite ephemeris errors which would otherwise corrupt ambiguity resolution and positioning in Sea-Based JPALS.

In the 2020 time frame, the Global Positioning System (GPS) will be fully modernized, and other satellite navigation systems will be operational. With an additional layer of fault detection, these systems will provide vertical guidance worldwide. This capability will be born of three important technologies. First and foremost, avionics will receive signals on two frequencies: L1/E1 and L5/E5a. This frequency diversity will do much to obviate the impact of ionospheric storms that troubles aviation use of GPS today. Secondly, a multiplicity of data broadcasts will be available to convey integrity information from the ground to the airborne users. These will include the navigation satellites themselves, geostationary satellites, and possibly terrestrial transmitters. However, the most important change will be the most subtle. The fault monitoring burden will be split between the aircraft and the supporting ground systems in a new way relative to the fault-detection techniques used in 2008. This new integrity allocation and the associated architectures are the subject of this paper.