Top 10 Key Metrics for Evaluating GNSS Navigation Chips

GNSS navigation chips are at the core of positioning systems used in smartphones, smartwatches, drones, robotics, vehicles, and many other connected devices. Their performance directly affects positioning accuracy, signal availability, acquisition speed, tracking stability, and overall system reliability.

When selecting a GNSS chip, looking only at positioning accuracy is not enough. GNSS chip performance depends on multiple factors, including sensitivity, Time to First Fix (TTFF), dynamic performance, observation accuracy, update rate, latency, power consumption, and resistance to interference.

This guide introduces 10 key metrics for GNSS chip evaluation and explains what each metric means, why it matters, and how it can be tested.

1. GNSS Chip Sensitivity: Tracking Weak Satellite Signals

GNSS sensitivity determines how well a chip can acquire and track weak satellite signals. It is particularly important in challenging environments such as urban canyons, indoor-adjacent areas, forests, and other locations with signal attenuation or obstruction.

Figure 1. Typical weak-signal environments—including elevated highways, tree canopies, and urban street canyons—place much higher demands on a chip's ability to acquire, track, and reacquire satellite signals.

Sensitivity is generally evaluated in three stages:

• Acquisition sensitivity: the weakest signal level at which the chip can initially detect and acquire satellites.
• Tracking sensitivity: the weakest signal level at which the chip can maintain satellite tracking.
• Reacquisition sensitivity: the signal level required for the chip to regain tracking after a temporary signal interruption.

GNSS chip sensitivity is typically specified in dBm, with more negative values representing weaker detectable signals.

A controlled GNSS signal simulator can be used to evaluate sensitivity. During testing, the signal power is gradually reduced until the receiver loses lock, while acquisition and reacquisition tests can be performed by resetting navigation data or temporarily interrupting the RF signal.

For applications operating in weak-signal environments, sensitivity should be evaluated together with tracking stability and positioning performance rather than considered as a standalone specification.

2. Time to First Fix (TTFF): How Quickly a GNSS Chip Acquires Position

Time to First Fix (TTFF) measures how long a GNSS chip takes to calculate a valid position after startup or signal interruption.

TTFF is commonly divided into three conditions:

• Cold start: No valid position, time, or current satellite navigation data is available. A typical cold start may take around 30 seconds under open-sky conditions.
• Warm start: Some valid satellite information is available, reducing the time required for acquisition. Typical performance may be around 10–20 seconds.
• Hot start: Recent satellite information and approximate position/time are retained, allowing a fix to be obtained much faster, often within several seconds.

TTFF can be tested using a GNSS simulator under repeatable conditions. Test procedures should define the starting state clearly because cold, warm, and hot starts produce significantly different results.

For battery-powered and time-sensitive devices, fast TTFF can improve user experience and reduce the time required before reliable positioning becomes available.

3. GNSS Positioning Accuracy: From Meter-Level to Centimeter-Level

GNSS positioning accuracy is one of the most important metrics when evaluating a GNSS chip.

Figure 2. Positioning Accuracy Comparison

The required accuracy depends strongly on the application. Typical positioning technologies include:

• Single Point Positioning (SPP): generally provides meter-level accuracy under open-sky conditions.
• SBAS: can improve positioning performance where supported correction services are available.
• PPP: can provide decimeter- to centimeter-level positioning depending on correction services, convergence conditions, and measurement environment.
• RTK: can achieve centimeter-level positioning when reliable correction data and carrier-phase measurements are available.
• PPP-RTK: combines wide-area correction services with fast ambiguity resolution and can support centimeter-level positioning in suitable environments.

Accuracy should be evaluated using clearly defined statistical metrics such as CEP, R95, RMS, or other application-specific confidence levels. These metrics should not be treated as interchangeable because they describe different statistical characteristics of positioning error.

For high-precision GNSS chip evaluation, testing can be performed using a GNSS simulator or a controlled dynamic test environment with a high-accuracy reference trajectory.

4. GNSS Dynamic Performance: Reliable Positioning Under High Dynamics

A GNSS chip may perform well under static conditions but behave differently when subjected to rapid movement.

Figure 3. High-dynamic applications require continuous satellite tracking and stable positioning without trajectory interruption or drift.

Dynamic performance evaluates how reliably the chip maintains positioning and tracking when the platform experiences high velocity, acceleration, deceleration, or rapid changes in direction.

Important parameters include:

• Maximum supported velocity
• Maximum acceleration
• Tracking stability during rapid movement
• Position and velocity accuracy
• Cycle slips and loss of lock
• Positioning latency
• Recovery performance after signal interruption

Dynamic testing is particularly important for UAVs, robotics, autonomous vehicles, and other high-speed platforms.

A GNSS simulator or hardware-in-the-loop (HIL) test system can reproduce high-dynamic trajectories, including rapid turns, acceleration, and deceleration, allowing GNSS chip performance to be evaluated under repeatable conditions.

5. Carrier-Phase and Pseudorange Accuracy: The Foundation of High-Precision Positioning

For high-precision applications, carrier-phase and pseudorange accuracy are critical GNSS chip performance metrics.

Pseudorange measurements provide the basic ranging information used for GNSS positioning, while carrier-phase measurements offer much finer measurement resolution and form the foundation of technologies such as RTK, PPP, and PPP-RTK.

Carrier-phase performance can be evaluated using parameters such as carrier-phase residuals and measurement noise.

A common laboratory approach is a zero-baseline test, where two identical GNSS receivers share the same antenna signal through an RF splitter. Because both receivers observe essentially the same satellite signals, common errors can be significantly reduced through differencing. The remaining residuals provide useful information about the receivers' intrinsic measurement noise.

For high-precision GNSS chips, low measurement noise and stable carrier-phase tracking are important for reliable ambiguity resolution and centimeter-level positioning.

6. GNSS Update Rate and Latency for Real-Time Control

Update rate and latency determine how quickly a GNSS chip can provide new positioning information and how closely that information represents the current state of the moving platform.

A 1 Hz update rate may be sufficient for many basic positioning applications, but higher update rates can be important for UAVs, robotics, autonomous vehicles, and real-time control systems.

Figure 4. High update rates and low latency are key indicators of a GNSS chip's real-time responsiveness and closed-loop control capability.

Modern GNSS chips may support update rates ranging from several hertz to tens or even 100 Hz, depending on the chip architecture and processing requirements.

When evaluating update rate, it is also important to measure:

• Positioning output frequency
• Data latency
• Timestamp accuracy
• Processing delay
• Synchronization with external sensors

For example, a system may output positioning data at 100 Hz but still have significant latency. Therefore, update rate and latency should be evaluated together rather than treating a high output frequency as sufficient evidence of real-time performance.

Hardware-in-the-loop testing and precise time synchronization can help measure end-to-end positioning latency.

7. GNSS Chip Power Consumption and Battery Life

Power consumption is a major consideration for battery-powered GNSS devices such as wearables, trackers, IoT devices, and portable equipment.

GNSS chip power consumption should be evaluated under different operating conditions rather than relying on a single typical value.

Key measurements include:

• Acquisition power consumption
• Continuous tracking power consumption
• High-performance positioning power consumption
• Sleep-mode power consumption
• Wake-up behavior
• Power consumption under different update rates

A programmable power supply can be used to measure current and voltage under controlled test conditions.

For compact devices, the optimal GNSS chip is not necessarily the one with the highest positioning performance. Power consumption, positioning requirements, update rate, and system workload must be considered together.

8. GNSS Anti-Interference and Anti-Spoofing Performance

GNSS signals are extremely weak when they reach the Earth's surface, making them vulnerable to intentional and unintentional interference.

Figure 5. Reliable anti-interference and anti-spoofing capabilities are essential for maintaining trustworthy positioning in challenging electromagnetic environments.

Anti-interference and anti-spoofing performance is therefore an important consideration for GNSS chips used in safety-critical, industrial, automotive, and other demanding applications.

Testing may include:

• Continuous-wave (CW) interference
• Broadband interference
• Swept-frequency interference
• Gaussian noise
• Signal jamming
• Spoofing scenarios
• Loss-of-lock and recovery testing

Interference performance can be evaluated by measuring the jammer-to-signal ratio, tracking stability, positioning accuracy, and time required to recover after interference is removed.

Anti-spoofing evaluation should also examine whether the receiver can detect abnormal GNSS signals or inconsistent navigation information instead of simply measuring whether the signal remains tracked.

9. GNSS Velocity Accuracy: Measuring Motion with Precision

GNSS velocity is primarily derived from satellite Doppler measurements and provides important information for moving platforms.

Velocity accuracy is particularly important for navigation systems, robotics, UAVs, autonomous vehicles, and integrated GNSS/INS systems.

Unlike position accuracy, GNSS velocity can remain highly useful even when position errors are relatively large. Stable velocity measurements can also improve the performance of integrated navigation systems.

Testing should compare the GNSS-derived velocity with a high-accuracy reference trajectory under both static and dynamic conditions.

Key evaluation parameters include:

• Velocity RMS error
• Velocity stability
• Performance during acceleration and deceleration
• Dynamic tracking behavior
• Noise and latency

The required velocity accuracy depends on the application. Automotive navigation, UAV control, surveying, and timing applications may have very different requirements.

10. GNSS Timing Accuracy and Time Synchronization

GNSS provides not only positioning but also highly accurate timing information.

GNSS timing accuracy is important for telecommunications, power systems, financial systems, industrial automation, data centers, and other applications that require precise synchronization.

Common timing-related parameters include:

• 1PPS accuracy
• UTC synchronization
• Internal clock stability
• Time-to-first-fix
• Timing jitter
• Holdover performance

Timing accuracy should be evaluated under clearly defined conditions, including satellite visibility, antenna configuration, correction services, and environmental conditions.

For systems requiring precise synchronization, 1PPS output and timestamp accuracy should be tested separately because they represent different aspects of timing performance.

How to Evaluate GNSS Chip Performance for Your Application

There is no single GNSS chip specification that determines overall performance.

A chip with excellent sensitivity may consume more power. A chip with a high update rate may require more processing resources. A high-precision chip may require additional correction data and more complex algorithms.

Therefore, GNSS chip selection should be based on the requirements of the target application, including:

• Required positioning accuracy
• Operating environment
• Signal availability
• Dynamic conditions
• Update rate and latency
• Power budget
• Interference environment
• Timing requirements
• System cost and integration requirements

The most meaningful GNSS chip evaluation combines multiple performance metrics under realistic operating conditions rather than relying on a single specification.

Qtalis develops GNSS solutions based on self-developed GNSS chip technologies, including the QC7820 and TC1720, supporting major global satellite constellations and high-precision positioning applications.

By evaluating the right performance metrics, engineers can select a GNSS chip that provides the appropriate balance of accuracy, reliability, power efficiency, and system performance for their specific application.

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