What Is GNSS Ambiguity Resolution? Understanding RTK Fix

Every RTK user has seen the positioning status change from Float to Fixed. But what exactly is being “fixed”?

A common misunderstanding is that RTK ambiguity fixing directly fixes the receiver’s coordinates. In reality, the receiver is not fixing its position—it is resolving the unknown integer ambiguity hidden inside GNSS carrier-phase measurements.

This integer ambiguity represents the unknown number of complete carrier cycles between the satellite and receiver. Once it is correctly estimated, the extremely precise information contained in carrier-phase observations can be fully utilized, allowing RTK systems to achieve centimeter-level positioning accuracy.

For applications such as surveying, UAV mapping, robotics, and autonomous systems, maintaining a reliable RTK Fixed solution is one of the most important factors determining positioning performance.

This article explains what GNSS ambiguity resolution is, why carrier-phase measurements require integer ambiguity estimation, and how modern RTK systems transition from Float to Fixed positioning.

1. What Is GNSS Ambiguity Resolution?

GNSS receivers mainly rely on two types of measurements:

• Pseudorange measurements
• Carrier-phase measurements

Both contain information about the distance between the satellite and receiver, but their accuracy characteristics are very different.

Pseudorange Measurement

Pseudorange estimates the signal travel distance from the satellite to the receiver.

It is relatively simple to obtain and is widely used in standard GNSS positioning. However, due to atmospheric effects, satellite errors, receiver noise, and other error sources, pseudorange positioning typically provides accuracy at the meter level.

Carrier-Phase Measurement

Carrier-phase measurements track the phase of the GNSS carrier signal itself.

Because GNSS carrier wavelengths are extremely short, phase measurements can theoretically provide millimeter-level precision. For example, the GPS L1 carrier wavelength is approximately 19 centimeters.

However, carrier phase has a fundamental limitation:

The receiver can accurately measure the change in signal phase, but it cannot immediately determine how many complete carrier cycles the signal has traveled before reaching the antenna.

This unknown number of complete cycles is called the integer ambiguity.

Understanding Integer Ambiguity

A simple analogy is measuring distance with a ruler that does not have a zero mark.

You can accurately measure every small movement after the initial measurement, but you do not know the absolute starting point.

GNSS carrier-phase observations work in a similar way:

• The fractional phase is measured with extremely high precision.
• The whole number of carrier cycles remains unknown.

The purpose of ambiguity resolution (AR) is to determine this missing integer value.

Once the integer ambiguity is correctly resolved, the receiver can fully recover the high precision information contained in the carrier-phase measurement.

Figure 1 – Carrier Phase Measurement

2. How Does GNSS Ambiguity Resolution Work?

The reason RTK systems can achieve centimeter-level accuracy is not because they directly measure position with centimeter precision.

Instead, they extract extremely precise information from carrier-phase observations by resolving the integer ambiguity.

Once the receiver knows:

• the fractional phase measurement, and
• the exact integer number of carrier cycles,

It can reconstruct the signal distance with very high precision.

In other words, the secret behind RTK Fixed positioning is not simply stronger satellite signals—it is the successful recovery of the hidden integer information inside carrier-phase measurements.

However, real GNSS environments are much more complicated than this simplified explanation.

Raw carrier-phase observations contain multiple error sources, including:

• Satellite orbit errors
• Satellite clock errors
• Receiver clock errors
• Ionospheric delay
• Tropospheric delay
• Multipath effects
• Receiver noise

These errors make it impossible to reliably determine integer ambiguities directly from raw observations.

To overcome this problem, RTK systems use advanced observation processing techniques, with double differencing being one of the most important methods.

2.1 Why RTK Uses Double Differencing

RTK positioning normally uses a base station and a rover receiver.

Because both receivers observe the same satellites at nearly the same time, many common errors can be eliminated through differencing.

Double differencing works in two stages.

First Difference: Between Base and Rover

The system first subtracts observations from the base station and rover for the same satellite.

This removes many satellite-related errors, including:

• Satellite clock errors
• Satellite orbit-related effects

Second Difference: Between Satellites

The system then performs another difference between different satellites.

This further reduces:

• Receiver clock errors
• Hardware-related biases

After double differencing, the remaining ambiguity terms regain their integer characteristics, making integer ambiguity estimation mathematically possible.

This is the foundation that allows RTK systems to determine whether a solution should be classified as Float or Fixed.

2.2 From Float to Fixed: How RTK Fix Is Achieved

After double differencing removes many common errors, the receiver can begin estimating the integer ambiguities.

However, the initial ambiguity estimate is not usually an integer value.

Instead, the receiver first obtains a float ambiguity solution.

For example, an estimated ambiguity value may be:

N=123.42

The receiver knows that the true ambiguity must be a whole number, but it does not yet know whether the correct value is:

$$123$$

or:

$$124$$

The challenge of ambiguity resolution is finding the most likely integer solution from many possible candidates.

The Role of the LAMBDA Algorithm

One of the most widely used ambiguity resolution methods in modern GNSS systems is the LAMBDA (Least-squares AMBiguity Decorrelation Adjustment) algorithm.

The basic process includes:

1. Estimating float ambiguities using filtering techniques
2. Analyzing the uncertainty relationship between ambiguities
3. Transforming the ambiguity search space through decorrelation
4. Searching for the most likely integer candidate
5. Validating the solution using statistical tests

In simple terms, LAMBDA makes the integer search problem more efficient by converting a highly correlated estimation problem into a more manageable search process.

Only when the best candidate solution is sufficiently more reliable than alternative solutions will the receiver accept the ambiguity as successfully resolved.

At this moment, the RTK solution status changes from:

Float → Fixed

The receiver can then provide stable centimeter-level positioning.

3. Challenges of Maintaining RTK Fixed Status

Achieving the first RTK fix is only part of the challenge.

For real-world applications, maintaining a reliable Fixed solution is often more difficult than obtaining the initial ambiguity resolution.

In environments such as urban areas, construction sites, forests, and indoor-outdoor transition zones, GNSS signals can change rapidly due to:

• Signal blockage
• Reflections
• Dynamic motion
• Atmospheric variation

These factors can interrupt carrier-phase tracking and force the receiver to resolve ambiguities again.

The performance of a modern RTK system is therefore determined not only by time-to-first-fix, but also by:

• Fix maintenance capability
• Re-fixing speed
• Robustness under signal degradation

3.1 Cycle Slips: Breaking Ambiguity Continuity

One of the most common causes of RTK fix loss is the cycle slip.

A cycle slip occurs when the receiver temporarily loses continuous carrier-phase tracking.

For example, when a vehicle passes behind a building or a UAV flies through an area with signal obstruction, the receiver may lose part of the carrier cycle count.

Because ambiguity resolution depends on maintaining continuous carrier-phase measurements, even a small interruption can make the previous ambiguity value invalid.

Once a cycle slip occurs:

• The previous Fixed solution may no longer be reliable.
• The receiver must detect the problem.
• Ambiguity resolution must be performed again.

For static surveying, occasional re-fixing may be acceptable.

However, for autonomous vehicles, robots, and UAVs, rapid recovery is critical because positioning errors can accumulate quickly during the re-fixing process.

3.2 Multipath: A Major Enemy of RTK Fixing

Another major challenge is multipath interference.

In an ideal environment, the receiver receives only the direct signal transmitted from the satellite.

However, in real-world environments, GNSS signals can reflect from:

• Buildings
• Glass surfaces
• Roads
• Bridges
• Metal structures

The receiver may then receive both:

• Direct signals
• Reflected signals

These reflected signals create additional phase errors and distort carrier-phase observations.

Because ambiguity resolution relies on extremely precise phase measurements, even small phase distortions can reduce fixing reliability.

To improve RTK performance, modern high-precision GNSS receivers typically combine multiple technologies, including:

• Multi-frequency GNSS observations
• Multi-constellation tracking
• Advanced multipath-resistant antennas
• Signal quality monitoring
• Adaptive filtering algorithms

Together, these technologies improve the probability of achieving and maintaining RTK Fixed status in challenging environments.

4. How GNSS/INS Integration Improves RTK Reliability

Although modern GNSS receivers have become significantly more robust, satellite signals can still be temporarily unavailable in challenging environments.

Examples include:

• Urban canyons
• Tunnels
• Underground areas
• Dense vegetation

This is where GNSS/INS integration becomes increasingly important.

An Inertial Measurement Unit (IMU) continuously measures:

• Acceleration
• Angular velocity
• Vehicle motion changes

Unlike GNSS, which depends on external satellite signals, the IMU can continue providing short-term motion information even during temporary signal interruptions.

By combining GNSS and INS measurements, integrated navigation systems can:

• Maintain smoother positioning during GNSS outages
• Reduce the impact of cycle slips
• Improve ambiguity re-fixing speed
• Increase overall navigation reliability

This is why GNSS/INS integration has become a key technology for:

• Autonomous driving
• Robotics
• UAV navigation
• Advanced surveying systems

For these applications, reliable positioning is not only about achieving a Fixed solution once—it is about maintaining that solution continuously during real-world operation.

5. Conclusion

GNSS ambiguity resolution is the foundation behind the transition from standard GNSS positioning to high-precision RTK solutions.

The term “RTK Fix” does not mean that the receiver has simply fixed its coordinates. Instead, it means that the system has successfully resolved the unknown integer ambiguities contained in carrier-phase measurements.

Once these integer ambiguities are correctly determined, the extremely precise information inside carrier-phase observations can be fully utilized, allowing RTK systems to achieve centimeter-level positioning accuracy.

However, achieving a Fixed solution is only the beginning. Maintaining reliable ambiguity resolution requires overcoming challenges such as:

• Cycle slips
• Multipath interference
• Satellite obstruction
• Atmospheric disturbances

Modern GNSS technologies—including multi-frequency observations, advanced algorithms such as LAMBDA, and GNSS/INS integration—continue to improve fixing speed, stability, and availability.

Ultimately, high-quality positioning is not determined only by how many satellites are visible. The real challenge is whether the receiver can successfully resolve and continuously maintain the carrier-phase ambiguities behind those signals.

That is what turns ordinary GNSS measurements into reliable high-precision positioning.

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