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Time to first fix

Time to first fix (TTFF) is a critical performance metric in global navigation satellite systems (GNSS), defined as the duration required for a receiver to acquire sufficient satellite signals, decode navigation data, and compute its initial position solution after power-on, reset, or signal interruption.^[1] This process enables the device to output a valid navigation fix, typically meeting criteria such as tracking a minimum number of satellites (e.g., four for GPS) and achieving acceptable position dilution of precision (PDOP).^[1] TTFF varies significantly based on the receiver's prior knowledge of satellite positions, time, and location, influencing its applicability in applications from consumer smartphones to autonomous vehicles. TTFF metrics are standardized but vary slightly by constellation (e.g., GPS almanac 12.5 min vs. others). TTFF performance is categorized into three primary start conditions, each reflecting different levels of retained data from previous operations: These categories are standard in GNSS testing and specifications, with cold starts being the longest due to the need to search all satellites without prior aiding data, often requiring full almanac collection which takes 12.5 minutes, though a fix can be achieved sooner with ephemeris alone.^[4] Several factors influence TTFF beyond start type, including environmental conditions like open sky versus urban canyons, which can delay signal acquisition, and receiver hardware efficiency in signal processing.^[2] Assisted GNSS (A-GNSS) techniques, such as providing ephemeris via cellular networks, can significantly reduce cold start TTFF in mobile devices. Shorter TTFF is essential for user experience in location-based services and safety-critical systems, where delays could impact emergency response or navigation accuracy.^[2] Ongoing advancements, including multi-constellation support (GPS, GLONASS, Galileo, BeiDou), further optimize TTFF by increasing visible satellites.^[1]

Definition and Fundamentals

Definition

Time to first fix (TTFF) is the elapsed time from the powering on or reset of a global navigation satellite system (GNSS) receiver until it delivers the initial usable position solution.^[5] This metric serves as a key performance indicator for GNSS receivers, capturing the startup phase before navigation begins.^[6] A valid first fix generally requires the receiver to acquire and track signals from at least four satellites, enabling the solution of unknowns including the receiver's three-dimensional position (latitude, longitude, and altitude) and clock bias relative to GNSS time.^[5] With fewer than four satellites, only partial solutions like two-dimensional positioning may be possible, but a full 3D fix demands this minimum for reliable navigation.^[7] The core process underlying TTFF encompasses signal acquisition, where the receiver detects and locks onto satellite transmissions; navigation data decoding, involving the extraction of ephemeris (precise orbital data) and almanac (approximate satellite positions) information; and position computation, which uses pseudorange measurements to triangulate the receiver's location.^[6] TTFF differs from related metrics, such as the interval for subsequent position updates (often governed by the receiver's update rate) or post-fix accuracy (which assesses the precision of computed positions over time).^[8]

Key Components

Time to first fix (TTFF) in a GNSS receiver is composed of several sequential phases that collectively enable the computation of an initial position solution. These phases include receiver warmup, satellite signal acquisition, signal tracking, navigation data decoding, and position solution computation. Each phase builds upon the previous one, with the overall process relying on the receiver's ability to process signals from multiple satellites to generate pseudoranges essential for positioning.^[9] The receiver warmup phase involves the initial activation and preparation of hardware and software components upon power-on. This includes loading firmware, allocating resources, and initializing internal clocks and oscillators to ready the system for signal processing. Without a successful warmup, subsequent operations cannot proceed, as it establishes the foundational state for the receiver.^[9]^[10] Satellite signal acquisition follows warmup and entails a two-dimensional search across possible code delays and Doppler frequency shifts to detect incoming GNSS signals from visible satellites. This phase typically requires identifying signals from at least four satellites, involving correlation of the received signal with locally generated replicas of the pseudorandom noise (PRN) codes, such as the C/A code, and estimating carrier phase alignments. Acquisition is crucial for initial signal detection but can be computationally intensive due to the uncertainty in satellite locations and frequencies.^[9]^[11]^[10] Once acquired, the signal tracking phase refines and maintains lock on the detected signals using feedback loops, such as delay-lock loops for code phase and phase-lock loops for carrier phase. This ensures stable measurement of pseudoranges and Doppler shifts while monitoring signal quality for potential losses. Tracking provides the continuous data stream necessary for decoding and is dependent on successful acquisition to initialize the loops.^[9]^[11] Navigation data decoding occurs during tracking and involves extracting the satellite's navigation message from the modulated signal, which includes the almanac for approximate satellite positions and orbits, and the ephemeris for precise orbital parameters valid over short periods. The almanac aids in predicting visible satellites, while ephemeris enables accurate range computations; decoding requires synchronization with the data bits and frames, often spanning multiple seconds per subframe. This phase is essential for providing the orbital information needed for position solving.^[9]^[10]^[11] Finally, position solution computation integrates the pseudoranges from at least four tracked satellites, along with decoded ephemeris and approximate receiver time and location, to solve for the three-dimensional position, velocity, and clock bias using methods like least-squares estimation. This phase depends on having synchronized pseudoranges from multiple satellites to resolve the nonlinear equations of trilateration, outputting the first valid fix upon convergence. The durations and efficiencies of these components vary depending on the start scenario, such as cold, warm, or hot starts.^[9]^[11]^[10]

Start Scenarios

Cold Start

In the cold start scenario, a GNSS receiver initializes with no prior navigation data, including no stored almanac, ephemeris, approximate time, or user position, necessitating a complete search across all possible satellite signals, Doppler shifts, and code phases to acquire any visible satellite.^[12]^[13] This state typically occurs after power-off events that clear memory, such as battery removal or factory reset, forcing the receiver to perform a blind acquisition without assistance from previous session data.^[12] The process begins with the receiver scanning the entire sky to detect and lock onto the signal of at least one satellite, after which it demodulates the navigation message to collect the almanac—a set of coarse orbital parameters for the entire constellation, broadcast at 50 bits per second (bps).^[12]^[4] Once the almanac is obtained, it enables the receiver to predict the approximate positions of visible satellites, allowing targeted tracking and subsequent download of precise ephemeris data for those satellites, which is essential for computing the initial position fix.^[14]^[15] The almanac collection alone requires up to 12.5 minutes to receive the full 25-page message, while ephemeris download adds about 30 seconds per satellite, as each set is transmitted in 30-second subframes.^[12]^[4] Overall, cold start time to first fix (TTFF) typically ranges from 30 seconds in optimal conditions with rapid acquisition to 12.5 minutes or more, dominated by the almanac download duration and extended by acquisition challenges or the need for multiple ephemeris sets from at least four satellites.^[12]^[14] This makes cold start the longest TTFF among start scenarios, contrasting with warm start where stored almanac data accelerates the process.^[15]

Warm Start

In a warm start scenario for GNSS receivers, the device retains a valid almanac, which provides approximate satellite orbital parameters, along with an estimated time accurate to within about 20 seconds and position within 100 km from a previous session, but lacks recent ephemeris data detailing precise satellite positions.^[12]^[4] This state allows the receiver to predict the visible satellites overhead without scanning the entire sky, limiting the signal acquisition search to a narrower set of pseudorandom noise codes and Doppler shifts.^[12] The process begins with the receiver using the stored almanac to identify and acquire signals from typically 3-4 visible satellites, after which it decodes the fresh ephemeris data broadcast by each satellite, a step that takes approximately 30 seconds per satellite.^[4] Once sufficient ephemeris is obtained, the receiver computes the initial position solution without needing to reacquire the full almanac, as the existing one remains valid for weeks.^[12] This contrasts with a cold start by skipping the lengthy almanac collection phase.^[4] Under typical open-sky conditions, the time to first fix (TTFF) in a warm start ranges from 20 to 40 seconds, primarily determined by the ephemeris download time, though it can extend to 2-3 minutes in challenging environments or with fewer visible satellites.^[12] This duration represents a significant reduction from cold start times, enabling faster navigation initialization in scenarios like brief power interruptions or receiver restarts after short downtime.^[13]

Hot Start

In the hot start scenario for GNSS receivers, the device retains recent and valid navigation data from a prior position fix, including precise ephemeris for satellite positions, approximate time, position, and velocity estimates, all typically valid within a 2-4 hour window.^[5]^[12] This state assumes minimal changes in the receiver's environment, such as the device remaining stationary or moving little, allowing it to avoid extensive data reacquisition.^[14] The hot start represents the fastest time to first fix (TTFF), often achieving a navigation solution in less than 1-5 seconds under optimal conditions, primarily involving signal relock and minor computational adjustments.^[5]^[15] This rapid performance stems from the receiver's ability to leverage intact data, contrasting with a warm start that requires downloading fresh ephemeris due to expired data.^[12] The process begins with the receiver using the last known position and velocity to predict visible satellites, followed by quick signal acquisition aided by stored ephemeris and frequency offset information.^[5] It then validates the ephemeris validity—generally lasting 2-4 hours—before computing an updated position, velocity, and time (PVT) solution with minimal decoding of new navigation messages.^[12] In standby modes, where oscillator temperature and time are preserved, the TTFF can approach 10 seconds even after short power-off periods of a few hours.^[14]

Factors Affecting TTFF

Receiver capabilities significantly influence the time to first fix (TTFF) in GNSS systems by determining how efficiently the receiver can perform signal acquisition. The number of channels and correlators enables parallel processing of multiple satellite signals, allowing simultaneous searches across code phases and Doppler shifts rather than sequential testing. For instance, receivers with higher channel counts, such as 48-channel designs, optimize signal-search concepts to achieve mean TTFF values around 2 minutes even after long interruptions, demonstrating reduced acquisition times through efficient constellation-wide searches.^[16] Increased channels also enhance acquisition sensitivity by combining signals from multiple frequencies and satellites, thereby shortening TTFF at lower carrier-to-noise ratios (C/N0).^[17] Similarly, greater processing power facilitates faster exploration of the extensive two-dimensional search space—spanning code delays (up to 1 ms for GPS C/A codes) and Doppler frequencies (typically ±10 kHz)—which is critical for acquisition and directly impacts TTFF duration.^[18] Software algorithms in the receiver further modulate TTFF through optimized search strategies during the acquisition phase. Sequential search methods evaluate code phase and Doppler hypotheses one at a time, leading to longer TTFF due to the exhaustive nature of the process, particularly in cold starts where prior data is unavailable. In contrast, parallel strategies, such as parallel code phase search (PCPS) using fast Fourier transforms (FFT), test multiple hypotheses simultaneously across frequency and time domains, substantially accelerating acquisition and reducing TTFF.^[19] These parallel approaches leverage hardware correlators to perform circular cross-correlations in the frequency domain, enabling coherent integration and detection of weaker signals more rapidly.^[20] Additionally, data storage mechanisms for retaining almanac and ephemeris information play a key role; persistent storage of this navigation data narrows the initial search space in warm or hot starts, avoiding full downloads and thus shortening TTFF compared to cold starts requiring complete reacquisition. Power management features in GNSS receivers can either aid or hinder TTFF depending on implementation, particularly in battery-constrained devices. Low-power modes, such as duty cycling or sleep states, reduce overall energy use by intermittently powering down acquisition and tracking circuits, but they often extend TTFF by forcing restarts from a cold state upon wake-up, as retained data may be lost and full signal reacquisition is needed.^[21] In contrast, optimized low-power designs that maintain minimal active processing during standby—while preserving ephemeris data—minimize acquisition phase duration and power draw, supporting faster TTFF in intermittent operation scenarios.^[18] These receiver-internal factors interact with start scenarios, where advanced capabilities like additional channels particularly accelerate cold starts by enabling broader parallel searches without prior assistance data.^[17]

Environmental and Signal Factors

Environmental and signal factors play a critical role in determining the time to first fix (TTFF) in global navigation satellite systems (GNSS), as they influence signal acquisition, ephemeris decoding, and position computation. Satellite geometry, quantified by the dilution of precision (DOP), affects TTFF by amplifying errors in pseudorange measurements; poor geometry (high DOP values, such as PDOP > 7) can delay the achievement of a reliable fix until sufficient satellites with favorable distribution are tracked, often requiring extended observation periods.^[22] Similarly, the number of visible satellites directly impacts availability; in scenarios with fewer than four satellites, acquisition and navigation solution computation are prolonged, exacerbating TTFF, particularly in obstructed environments where multi-constellation support (e.g., GPS + Galileo) can mitigate this by increasing tracked satellites to an average of 8 or more.^[23] Atmospheric delays further complicate signal processing and extend TTFF. Ionospheric delays, caused by refraction from charged particles, introduce frequency-dependent errors (inversely proportional to f²) up to 4 meters in pseudorange, which can hinder satellite lock and ambiguity resolution during acquisition, especially under high solar activity.^[24] Tropospheric delays, non-dispersive and stemming from neutral atmosphere refraction (wet and dry components totaling 2-3 meters zenith delay), equally affect all frequencies and primarily impact vertical accuracy, but residual errors in real-time positioning increase noise, delaying the first fix by complicating pseudorange corrections.^[24] Urban canyons and similar environments degrade GNSS performance through signal blockage and multipath propagation, significantly prolonging TTFF. Tall structures limit satellite visibility to as few as 2-3 per session, forcing reliance on non-line-of-sight (NLOS) signals with high variability in signal-to-noise ratio (SNR), which extends acquisition time due to increased blackout probabilities and the need for extended integration.^[25] Multipath reflections from buildings cause SNR fluctuations and pseudorange biases, further delaying navigation message decoding and fix computation in these settings.^[25] In foliage-attenuated or indoor scenarios, signal attenuation (10-30 dB through materials like cinder blocks or leaves) reduces SNR to levels as low as -18 dB, necessitating longer coherent integration times (up to hundreds of milliseconds) for detection, thereby increasing TTFF by orders of magnitude compared to open-sky conditions.^[26] Differences across GNSS constellations, such as GPS and Galileo, arise from variations in signal power and data rates, influencing TTFF robustness. GPS L1 signals exhibit strong TTFF performance (e.g., average 31.9 seconds at 0 dB-Hz C/N0), benefiting from higher effective power under attenuation and tracking more satellites (average 8.1), which supports faster acquisition in challenging conditions.^[27] In contrast, Galileo signals, while offering improved error correction via Reed-Solomon coding and reduced clock/ephemeris data (RedCED) in the I/NAV message, result in longer TTFF (e.g., 80.9 seconds at 0 dB-Hz) due to fewer tracked satellites (average 5.0) and higher baseline data rates on E1-B (125 bps versus GPS L1 C/A's 50 bps), though modern bands like E5a achieve low effective rates (~21.4 bps) for comparable demodulation times around 53 seconds.^[27]^[28]^[29] These characteristics make GPS more resilient in cold starts, where environmental factors already heighten acquisition challenges.^[27] Emerging low Earth orbit (LEO) PNT systems, such as those proposed by TrustPoint and integrated with 6G non-terrestrial networks, represent a new signal factor that substantially reduces TTFF as of 2025. These systems provide stronger signal strengths (up to 20-30 dB higher than traditional GNSS), larger bandwidths, and denser satellite constellations, enabling acquisition times under 1 second even in cold starts and urban environments, while improving multipath resolution and jamming resistance.^[30]^[31]

Measurement and Calculation

TTFF Budget Breakdown

The time to first fix (TTFF) in GNSS receivers can be mathematically decomposed into additive components that represent the sequential phases required to achieve a navigation solution. The core equation is given by

\text{TTFF} = T_{\text{warmup}} + T_{\text{acquisition}} + T_{\text{tracking}} + T_{\text{decoding}} + T_{\text{solution}},

where each term corresponds to a distinct stage in the receiver's initialization and signal processing pipeline.^[5] T_{\text{warmup}} denotes the initial hardware and software initialization time, typically ranging from 1 to 10 seconds depending on the receiver's design and power-up sequence. This phase ensures the receiver's oscillators stabilize and basic functions are loaded before signal processing begins.^[5] T_{\text{acquisition}} is the time spent searching for and detecting visible satellite signals, which involves correlating the received signal with locally generated replicas across possible code delays and Doppler shifts. This duration is heavily influenced by the search space size, calculated as the product of the number of Doppler frequency bins (N_f, determined by Doppler uncertainty \Delta f = 2 f_{d,\text{MAX}} and resolution \delta f = 1/T, where T is the integration time) and code phase bins (N_T, spanning the code length with resolution \delta t \approx 0.5 chips), divided by the number of parallel correlators P: N = N_f N_T / P. Larger uncertainties in Doppler (e.g., up to ±10 kHz in cold starts) and code phase expand the search space, potentially extending T_{\text{acquisition}} from milliseconds in assisted scenarios to tens of seconds unaided.^[32]^[5] T_{\text{tracking}} represents the settling time for the code and carrier tracking loops to achieve stable synchronization, usually 1 to 5 seconds, allowing the receiver to maintain lock on the detected signals with sufficient precision for data demodulation.^[5]^[32] T_{\text{decoding}} encompasses the time to demodulate and process the navigation message, including sub-components for almanac collection (coarse satellite orbit data from all constellations, requiring up to 25 pages at 50 bits per second, or approximately 750 seconds in unaided cold starts) and ephemeris download (precise orbit data per satellite, about 30 seconds each). This phase dominates in scenarios lacking prior data, as the almanac enables targeted ephemeris acquisition from visible satellites.^[5]^[33] Finally, T_{\text{solution}} is the computation time for the position-velocity-time (PVT) solution using least-squares or Kalman filtering once sufficient ephemerides and pseudoranges are available, typically under 1 second for standard receivers.^[5] In a representative cold start without assistance, the TTFF budget is dominated by T_{\text{decoding}} (around 720 seconds for almanac collection), with T_{\text{acquisition}} and other terms contributing minimally, yielding a total of approximately 12-15 minutes. For a warm start with stored almanac but no recent ephemeris, the budget shifts to T_{\text{acquisition}} and T_{\text{tracking}} (each ~10-20 seconds), plus ephemeris decoding (~30 seconds per satellite for 4-6 needed), resulting in a total TTFF of about 30-60 seconds.^[33]^[5]^[14]

Testing and Estimation Methods

Direct testing of Time to First Fix (TTFF) in GNSS receivers typically involves using signal generators or simulators to replicate real-world scenarios, measuring the duration from receiver power-on to the output of a valid 3D position fix.^[1] This process employs hardware like software-defined radios (SDRs) and automated scripts to cycle through multiple trials—often at least 200 per start condition (cold, warm, or hot)—under controlled parameters such as satellite constellations, signal attenuation, and interference levels, with metrics like mean TTFF and 95th percentile values recorded for statistical reliability.^[1] Aviation-specific standards like RTCA DO-229D specify minimum operational performance requirements, including TTFF thresholds for airborne receivers under varying environmental conditions.^[34] Simulation and estimation methods rely on theoretical models to predict TTFF without physical hardware, particularly by modeling the acquisition phase through the search space of possible code delays and Doppler shifts. The total search space is quantified as the product of frequency and code bins, N = \frac{\Delta f}{\delta f} \cdot \frac{\Delta t}{\delta t}, where \Delta f is the Doppler range, \delta f the bin width, \Delta t the code length, and \delta t the chip resolution, leading to approximations like TTFF \approx \frac{N}{\text{search rate}} + T_{\text{decoding}} for the acquisition and data decoding times in cold starts.^[32] These models, extended from serial or parallel acquisition theories, incorporate factors like coherent integration time and false alarm penalties, and are validated by comparing simulated TTFF distributions (e.g., 95% confidence levels) against measurements from real receivers like those processing GPS L1 C/A or Galileo E1 signals.^[32] Metrics for TTFF robustness evaluate performance under adverse conditions, such as signal attenuation or limited satellite visibility, with recent 2025 studies highlighting multi-GNSS configurations' resilience. In one such analysis using a u-blox ZED-F9P receiver and Spirent GSS6450 simulator, cold-start TTFF was tested across GPS, GLONASS, BeiDou, and Galileo under 0-20 dB attenuation, revealing GPS as most robust (e.g., 31.9 s at 0 dB to 51.3 s at 20 dB) with low positioning errors (~2.24 m), while Galileo showed higher vulnerability (80.9 s at 0 dB to 583 s at 20 dB).^[35] These tests, involving over 42,000 runs, underscore the need for multi-constellation tracking to maintain TTFF below critical thresholds in degraded environments, informing resilience standards for diverse applications.^[35]

Applications and Enhancements

Importance in GNSS Systems

Time to first fix (TTFF) is particularly critical in time-sensitive applications where rapid positioning is essential for safety and operational efficiency. In emergency location services such as E911, a short TTFF enables quick determination of a caller's position, potentially reducing response times in life-threatening situations; without assistance, it can take several minutes, delaying critical interventions.^[36] For autonomous vehicles and advanced driver-assistance systems (ADAS), fast TTFF ensures immediate accurate positioning upon startup or exit from signal-obscured areas like garages, minimizing safety risks from delayed navigation.^[37] Similarly, in drones and unmanned aerial vehicles (UAVs), TTFF determines how swiftly the system achieves altitude awareness and navigation post-power-on, vital for mission initiation, safe flight paths, and return-to-base operations.^[38] TTFF significantly influences user experience in consumer devices like smartphones and wearables, where seamless integration into daily activities is expected. A reduced TTFF allows navigation apps to provide instant location-based services upon launch, enhancing usability in scenarios such as turn-by-turn directions or fitness tracking. Conversely, prolonged TTFF can lead to user frustration, as delays in acquiring a fix disrupt app performance and perceived device reliability.^[39]^[40] At the system level, TTFF plays a key role in multi-constellation GNSS setups combining GPS, Galileo, and BeiDou, which enhance global reliability by increasing satellite visibility and reducing acquisition times for more robust positioning worldwide. This integration mitigates single-system vulnerabilities, ensuring consistent performance across diverse geographies and improving overall GNSS dependability for critical infrastructure.^[41]^[42]

Techniques to Reduce TTFF

Assisted GNSS (A-GNSS) leverages external data sources, such as cellular networks or Wi-Fi, to provide receivers with critical assistance information including satellite almanacs, ephemerides, approximate time, and initial position estimates, thereby accelerating the acquisition process particularly in cold starts.^[43] This assistance dramatically shortens the time required to download and process navigation data, reducing cold start TTFF from potentially tens of seconds or more in standalone mode to under 10 seconds in urban environments with reliable connectivity.^[44] For instance, A-GNSS enables smartphones to obtain fixes in as little as 5 seconds by prioritizing visible satellites and Doppler predictions, enhancing usability in location-based services.^[45] Multi-frequency receivers exploit signals from multiple bands, such as GPS L1 and L5 or Galileo E1 and E5a, to improve acquisition speed through better ionospheric error mitigation and higher signal robustness, allowing parallel processing that cuts search times compared to single-frequency systems.^[46] The L5 band, with its wider bandwidth and pilot component, offers higher robustness but is generally more complex to acquire than L1 without assistance; with precise Doppler aid, it can achieve faster synchronization in high-sensitivity conditions.^[47] Furthermore, integrating these receivers with inertial sensors in hybrid GNSS/INS systems provides interim position estimates during signal outages or weak acquisition phases, enabling a first fix in seconds even in challenging scenarios like urban canyons.^[48] This fusion uses inertial measurement unit (IMU) data to predict satellite geometry, significantly reducing overall TTFF in tightly coupled architectures. The evolution of TTFF reduction techniques traces back to the 1980s, when standalone GPS receivers required minutes-long acquisitions due to exhaustive searches over unknown ephemeris and time parameters without external aid.^[49] By the 2000s, the introduction of A-GNSS marked a pivotal shift, bringing TTFF down to seconds via network assistance, while the proliferation of multi-GNSS constellations—integrating GPS, GLONASS, Galileo, and BeiDou—by the 2010s increased visible satellites, further reducing acquisition times through diversified signal availability.^[50] As of 2025, research into AI and machine learning for GNSS signal processing is advancing, with applications in optimizing acquisition and navigation in complex environments for high-demand applications like autonomous vehicles.^[51] Recent developments include Galileo's improved I/NAV message (implemented in 2023), which reduces TTFF, and integration with low-Earth orbit (LEO) satellites for enhanced visibility and faster fixes in multi-GNSS systems.^[27]^[52]

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Long TTFF results in an increased frustration level of the users. This long TTFF can be improved by using an external LNA. Resume, GPS receivers suffer a ...
[40]
Global Navigation Satellite Systems - Aker Technology USA
TCXOs often feature fast start-up characteristics, helping receivers reach a stable state more quickly and reducing TTFF, which enhances the user experience.
[41]
https://www.sepltd.com/news/is-gnss-better-than-gps/
[42]
What is Time to First Fix (TTFF) in the World of GNSS/GPS Antennas?
Time to First Fix (TTFF) is the time a GPS device takes to pinpoint its position from satellites after being turned on.
[43]
Performance of Assisted-Global Navigation Satellite System from ...
Jan 15, 2024 · A receiver with prior knowledge of these frequency and code variables reduce the TTFF. For example, for a cold start without information, the ...
[44]
Multi-frequency smartphone positioning performance evaluation
Aug 5, 2024 · A-GNSS positioning can reduce the TTFF from 30 to under 5 s, representing an improvement of over 85% in the cold start speed compared to a ...
[45]
Assisted GNSS (A-GNSS) - u-blox
Jun 2, 2025 · Assisted GNSS (A-GNSS) speeds up the signal acquisition process and shortens the time needed to achieve a first position fix.
[46]
[PDF] Modern GNSS/GPS signals: moving from single-band to dual-band
This white paper explores the transition from single-band to dual-band GNSS (global navigation satellite systems) technology. It delves into the evolution ...
[47]
Comparison of L1 and L5 Bands GNSS Signals Acquisition - PMC
The goal of this paper is therefore to compare the acquisition of L1 and L5 bands signals (GPS L1 C/A and L5, Galileo E1 and E5a/b) to determine which one is ...Missing: TTFF inertial hybrid
[48]
Full article: Tightly coupled multi-frequency PPP-RTK/INS integration ...
The results show that by introducing MF observations, the PPP fixed solution gains a significant improvement in both the positioning accuracy and Time of The ...
[49]
Improving TTFF by two-satellite GNSS positioning - ResearchGate
Aug 6, 2025 · The article presents the results of real simulation studies, assessing the impact of Doppler shift on the accuracy of the designated positions ...
[50]
Open Source GNSS Reference Server for Assisted-Global ...
Nov 26, 2010 · The TTFF counts the time between when the cold start command is sent and when a valid 3D position is reported. The standalone GPS test is ...<|separator|>
[51]
[PDF] GNSS User Technology: State-of-the-Art and Future Trends
To reduce that TTFF, current GNSS receivers download. A-GNSS data, which greatly reduces the amount of signal needed to obtain a first fix to milliseconds [174] ...
[52]
Optimised Signal Selection Algorithm for Acquisition and Re ... - MDPI
Jun 5, 2025 · The results show better satellite geometry and quicker re-acquisition of satellites/signals using the optimal list of satellites and signals.Missing: sources | Show results with:sources