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Institute of Navigation The world's premier professional society advancing positioning, navigation, and timing (PNT).

Every year, the 𝗜𝗢𝗡 𝗔𝗻𝗻𝘂𝗮𝗹 𝗔𝘄𝗮𝗿𝗱𝘀 recognize the people moving positioning, navigation, and timing forward. Nominations f...
10/14/2026

Every year, the 𝗜𝗢𝗡 𝗔𝗻𝗻𝘂𝗮𝗹 𝗔𝘄𝗮𝗿𝗱𝘀 recognize the people moving positioning, navigation, and timing forward. Nominations for the 2026 awards close tomorrow, October 15, and this is your 𝗙𝗜𝗡𝗔𝗟 𝗥𝗘𝗠𝗜𝗡𝗗𝗘𝗥 to recognize someone who has made a lasting impact on the field.

Swipe through to celebrate our 2025 recipients:

𝗕𝘂𝗿𝗸𝗮 𝗔𝘄𝗮𝗿𝗱: Dr. Sharbel Kozhaya, Joe Saroufim*, and Dr. Zaher (Zak) M. Kassas, for their paper, "Unveiling Starlink for PNT," published in the Spring 2025 issue of 𝙉𝘼𝙑𝙄𝙂𝘼𝙏𝙄𝙊𝙉, Journal of the Institute of Navigation

𝗛𝗮𝘆𝘀 𝗔𝘄𝗮𝗿𝗱: Francisco Javier Benedicto Ruiz, for visionary leadership and sustained contributions that enabled EGNOS, Galileo, and the definition of
next-generation navigation, securing Europe’s global leadership in satellite navigation

𝗣𝗲𝗿 𝗘𝗻𝗴𝗲 𝗘𝗮𝗿𝗹𝘆 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁 𝗔𝘄𝗮𝗿𝗱: Dr. Rong Yang*, for the advancement of GNSS resilience in challenging environments

𝗣𝗧𝗧𝗜 𝗗𝗶𝘀𝘁𝗶𝗻𝗴𝘂𝗶𝘀𝗵𝗲𝗱 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗔𝘄𝗮𝗿𝗱: Dr. James Camparo, for excellence in collaboration and education in addressing technical risk in the application of atomic clocks for space-based position, navigation, and timing

𝗦𝘂𝗽𝗲𝗿𝗶𝗼𝗿 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁 𝗔𝘄𝗮𝗿𝗱: Captain Celestia P. Holguin*, for improved MC-130 student flight training outcomes, and pioneered innovative airdrop procedures

𝗧𝗵𝘂𝗿𝗹𝗼𝘄 𝗔𝘄𝗮𝗿𝗱: Dr. Daniele Borio, for pioneering multidimensional GNSS meta-signal processing using hypercomplex numbers, enabling optimal multi-frequency signal reconstruction, robust measurement techniques adopted by industry, and advancing receiver design

𝗧𝘆𝗰𝗵𝗼 𝗕𝗿𝗮𝗵𝗲 𝗔𝘄𝗮𝗿𝗱: Dr. Todd A. Ely, for seminal contributions to the advancement of autonomous space navigation technologies, including the Deep Space Atomic Clock, and one-way uplink radiometric tracking in lunar orbit

𝗪𝗲𝗲𝗺𝘀 𝗔𝘄𝗮𝗿𝗱: Matt Harris, for significant and sustained contributions to the development and standardization of GNSS for aviation applications

*Not pictured

𝗦𝘂𝗯𝗺𝗶𝘁 𝘆𝗼𝘂𝗿 𝗻𝗼𝗺𝗶𝗻𝗮𝘁𝗶𝗼𝗻: ion.org/awards

09/25/2026

ION GNSS+ 2026: A packed plenary, a full exhibit hall, an evening with ION PNT masters, students presenting alongside engineers whose work they grew up reading, and a 40th meeting anniversary Trivia Night Celebration with the ION Satellite Division and its founders.

Congratulations to Dr. Alison Brown, recipient of the Johannes Kepler Award; Dr. Zachary Clements, recipient of the Bradford W. Parkinson Award; Faezeh Mooseli and Joe Saroufim, of The Ohio State University, winners of the ION GNSS+ 2026 Best Student Paper Award; and Dr. Dorota Grejner-Brzezinska, who was recognized for her years of service to the ION’s Satellite Division. All received their awards at Friday's awards luncheon.

Thank you to the Program Committee and the Satellite Division Executive Committee, whose volunteer work makes this meeting possible, as well as to our exhibitors, sponsors, media partners, and corporate members who showed up in force.

Here is a look back at the week.

Welcome to the newly elected Satellite Division officers. See you at ION GNSS+ 2027!

The Bradford W. Parkinson Award, awarded annually to an outstanding graduate student in the field of global navigation s...
09/21/2026

The Bradford W. Parkinson Award, awarded annually to an outstanding graduate student in the field of global navigation satellite systems (GNSS). This award, which honors Dr. Parkinson for his leadership in establishing both the U.S. Global Positioning System and the Satellite Division of the Institute of Navigation, was presented to Dr. Zachary Clements, The University of Texas at Austin, for his dissertation: GNSS Interference Detection and Geolocation.

Johannes Kepler Award, sponsored by the Satellite Division of the Institute of Navigation to honor an individual for sus...
09/21/2026

Johannes Kepler Award, sponsored by the Satellite Division of the Institute of Navigation to honor an individual for sustained and significant contributions to the development of satellite navigation during their lifetime, was presented during ION GNSS+ 2026 in Orlando, Florida, to Dr. Alison Brown for her sustained record of pioneering technical innovations, operational deployments, strategic leadership, and PNT community advancement.

Heading to the Small Satellite Conference this month? The Institute of Navigation will be there August 23-26 in Salt Lak...
08/13/2026

Heading to the Small Satellite Conference this month?

The Institute of Navigation will be there August 23-26 in Salt Lake City at Booth 8.

Add us to your list. Stop by to talk PNT, the NAVIGATION journal, and what's ahead at ION GNSS+ 2026 in Orlando.

We'd love to meet you.

How long can a spacecraft keep watching a single pulsar before its own clock corrupts the measurement?As missions return...
08/12/2026

How long can a spacecraft keep watching a single pulsar before its own clock corrupts the measurement?

As missions return to the Moon and push deeper into space, navigation resources are stretched — the Deep Space Network is at times up to 40% oversubscribed. That has driven interest in autonomous alternatives like X-ray pulsar navigation (XNAV), which uses X-ray millisecond pulsars (MSPs) as signals of opportunity. But XNAV needs long integration times to form a usable measurement, and over those windows, error from the onboard clock accumulates unchecked.

Kyle J. Houser and Demoz Gebre-Egziabher (University of Minnesota) quantify how clock quality sets the limit on usable observation time. In a Monte Carlo simulation, a maximum-likelihood estimator (MLE) recovers phase and frequency from simulated photon arrival times corrupted by a two-state, frequency random walk clock error model. The estimator's error is compared against the Cramér–Rao lower bound (CRLB) across four oscillators — a TCXO, an OCXO, a Microchip SA65 chip-scale atomic clock (CSAC), and a cesium clock — using the pulsar PSR B1937+21.

In the authors' words: "How long can a pulsar be viewed without estimating or correcting clock errors before timing noise dominates the measurement?"

Each oscillator maps to a usable window: the TCXO is unsuitable, the OCXO holds for roughly 1,000–20,000 s, the CSAC stays converged to the CRLB until about 50,000 s, and the cesium clock is nearly indistinguishable from clean data. That distinction matters for small satellites, where a cesium clock is hard to fit within size, weight, power, and cost (SWAP-C) constraints.

Read the full open-access article in NAVIGATION:
https://doi.org/10.33012/navi.773

What happens to a UAV's navigation when GNSS is jammed and the vehicle is moving too fast for standard visual methods to...
08/05/2026

What happens to a UAV's navigation when GNSS is jammed and the vehicle is moving too fast for standard visual methods to keep up?

GNSS sensors are vulnerable to signal jamming and to the changing positions of satellites. Systems relying solely on an inertial measurement unit (IMU) accumulate positioning error that can reach the kilometer scale. Standard SLAM methods don't apply either: because the UAV moves at high speed along all three axes, the background continuously changes.

Ali Güven and İmam Şamil Yetik (TOBB Economics and Technology University, Ankara) present a camera-only navigation solution for continuously operating high-speed UAVs — the paper frames the problem as optimal route navigation for UAVs such as missiles or drones.

SuperPoint extracts features and LightGlue matches UAV camera images to reference satellite images. Two methods are introduced here: reference image optimization (RIO), which autonomously selects the reference images, and feature anomaly detection (FAD), which eliminates matched features inconsistent with camera movement. Between matching cycles, an XGBoost model tracks points using translation and rotation changes derived from homography estimation.

In the authors' words: "The results in Table 3 indicate that the proposed method does not exhibit the best tracking performance based on pixel error, but is very close to the best-performing method with a considerably lower computation time."

Evaluated entirely in simulation — Unreal Engine environments streamed via AirSim, plus Google Earth imagery — with runtimes measured on an Nvidia Jetson AGX Xavier. Reported target-based navigation error: 14.82 ± 2.42 m.

Read the full open-access article in NAVIGATION:
https://lnkd.in/eUYabKeW

When you're validating a high-precision GNSS solution, how much should you trust the resolved integer ambiguities — espe...
07/29/2026

When you're validating a high-precision GNSS solution, how much should you trust the resolved integer ambiguities — especially when you're not fully confident they're correct?

Model validation is what catches the unmodeled effects — a blunder in a pseudorange, a carrier-phase cycle slip, or an atmosphere delay that isn't fully corrected — that bias the estimated parameters, such as user position coordinates, when they remain unnoticed. Two common approaches each have a catch. The ambiguity-float (AF) approach ignores the integer nature of the ambiguities, so validation can't benefit from those constraints. The alternative assumes the ambiguities are known, which only holds when the resolution success rate is very close to one.

Chengyu Yin, Peter Teunissen, and Christian Tiberius (Delft University of Technology, with Teunissen also at Melbourne and Curtin) take up a middle path. Their paper shows how to apply two AR-based parameter significance tests — the ARs test, which uses a high-probability-density acceptance region, and the ARn test, which uses a continuous ellipsoidal one — both of which use the distribution of the resolved ambiguities. They evaluate detection power against the AF and ambiguity-known (AK) tests across blunders, cycle slips, and ionosphere and troposphere delays.

In the authors' words: "the AR significance tests can perform better than the AF test, even if the success rate is not close to one."

The results come from Monte Carlo experiments on a single-constellation GPS double-differenced model. The advantage isn't universal — the AR test can sometimes trail the AF test, so the authors give an easy-to-compute criterion for the blunders and cycle slips tests to predict which case you're in. For atmosphere delays, where the power functions turn spiky, they show that a partial ARs (PARs) test — resolving a subset of the ambiguities — keeps the power function smooth, and that combining the ARs and PARs tests always outperforms either alone.

Read the full open-access article in NAVIGATION: https://lnkd.in/eFwCG8vT

How does a self-driving car stay in its lane when the buildings around it are scrambling its satellite signals?In dense ...
07/22/2026

How does a self-driving car stay in its lane when the buildings around it are scrambling its satellite signals?

In dense cities, GNSS signals reflect off building faces before reaching the receiver, corrupting the measurements a vehicle relies on for absolute positioning. Autonomous driving demands tight localization — the paper cites a horizontal 95% accuracy requirement of 0.21 m for autonomous vehicle operations (Reid et al.). And when more than half the satellites in view are non-line-of-sight (NLOS), conventional robust methods reach their breakdown point and the position solution degrades.

Fabian Ruwisch and Steffen Schön of the Institut für Erdmessung (Institute of Geodesy) at Leibniz Universität Hannover address this by pairing stored map information with robust estimation for GNSS RTK positioning.

Their approach introduces the HG-estimator, a new robust estimator combining the Huber and Geman–McClure loss functions. It is embedded in GNSS feature map-aided weighting (GNSS FMA-W), where a GNSS feature map supplies a prior on each satellite's expected pseudorange residual along the route. That prior lets the weight model down-weight corrupted signals rather than excluding them outright.

The method was validated on two real automotive test drives in Hannover — a medium and a deep urban trench with line-of-sight satellite availability below 50%. Combining the GNSS feature map with the HG-estimator improved horizontal accuracy by 54% and 60% over C/N0 weighting respectively, and was the only tested method to meet lane-determination requirements in the deep trench.

Read the full open-access article in NAVIGATION: https://doi.org/10.33012/navi.779

Happy Independence Day from everyone at the Institute of Navigation!As millions travel by road, air, and sea this Fourth...
07/03/2026

Happy Independence Day from everyone at the Institute of Navigation!

As millions travel by road, air, and sea this Fourth of July to be with family and friends, it's worth a quiet nod to the positioning, navigation, and timing technology quietly guiding the way.

Wishing our members celebrating the holiday a safe, happy holiday.

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