Recent years have shown that Low-Earth Orbit (LEO) satellites are becoming the leading idea for the future of the space industry, gathering heavy investment from technology giants, as seen from several providers of mega-constellations, such as SpaceX (Starlink), Eutelsat (OneWeb), Iridium, or Amazon (Kuiper). LEO satellites are suitable not only for communication purposes, but they also hold a strong potential for Positioning, Navigation and Timing (PNT) applications, as their proximity to Earth results in fast satellite movements in orbit as well as in high received signal strengths, which may translate into better PNT signals compared to already available alternatives. In this work, we show the viability of LEO-PNT constellations by providing a comprehensive performance comparison based on coverage, Dilution of Precision (DOP) and Carrier-to-Noise Ratio (/0) metrics between several existing and upcoming constellations, as well as two theoretical LEO-PNT constellations, by considering them as dedicated LEO-PNT systems. Our results show that, among the existing and upcoming LEO constellations, Starlink, OneWeb, Xona and Centispace show great promise for future PNT solutions, and that alternative designs that are on par, or perhaps even better, are still possible.
capability for global coverage, and their potential for flexible, scenario-specific designs, e.g. through
optimization methods [
The current LEO landscape includes new constellations such as Centispace [15, 16] and Xona [17],
as well as older constellations such as Orbcomm [18], Iridium [19], Globalstar [20], Starlink [
Motivated by the fact that very few performance comparisons among LEO-PNT constellations have been
published so far, we present a simulation-based extensive comparison of several LEO-PNT performance
metrics for eight LEO satellite constellations (one as the GNSS benchmark, three selected among
existing mega-constellations, two selected among on-going LEO-PNT designs and two experimental
ones, based on prior work by the Authors). The comparisons are made with a MATLAB-based [33]
in-house developed constellation simulator (see section 2.3), under several indoor/outdoor scenarios.
Our main contributions are:
• Providing an extensive performance comparison, based on coverage, Dilution of Precision (DOP),
and Carrier-to-Noise Ratio (/0) metrics between nine constellations, based on three types
of models: models relying on existing mega-constellations (Kuiper, OneWeb, Starlink), models
relying on existing smaller-sized LEO-PNT constellations (Centispace and Xona) and Authors’
derived models, based on direct parameter optimization [
As mentioned in subsection 1.3, our study uses the Galileo constellation as the GNSS benchmark, and includes 7 known LEO constellations: 3 mega constellations, 2 smaller-scale constellations, and 2 experimental ones. Even if possibly outdated, the constellation parameters (i.e., orbital altitude, number of satellites, number of orbital planes, phasing angle between orbital planes, inclination angle of the orbital plane, constellation topology, Right Ascension of the Ascending Node (RAAN) and eccentricity) for the existing constellations can be obtained from public sources, with some exceptions. Most of the relevant parameters for Xona were published in their patent application [35], however a few parameters, i.e. the altitude and satellite’s exact operating Efective Isotropic Radiated Power ( EIRP), are not given exactly. In a similar manner, to the best of the Authors’ knowledge, the exact channel parameters for Centispace are also not available publicly. Therefore, some assumptions were made as seen in Table 1 in order to fill the gaps. Since Centispace has been designed as an augmentation system for Beidou, we assume that the missing parameters are similar to Beidou’s B1 band. As for Xona, the orbital plane altitude is taken as the mentioned upper limit from [35], and the channel parameters are again assumed to be similar to Beidou’s for comparison purposes with Centispace’s constellation design.
In addition to the mentioned known constellations, we provide 2 experimental single-shell LEO-PNT
constellation designs, that have been obtained in our earlier studies [
In order to evaluate the performance of LEO-PNT constellations we selected metrics that are related to the geometry between the users and the satellites, as well as to the reception quality of the received signal. The metrics that we selected for our comparisons are: coverage, Geometric Dilution of Precision (GDOP), Position (3D) Dilution of Precision (PDOP) and /0.
The coverage reflects the signal-reception percentage; for most PNT solutions, a good reception requires having at least 4 satellites in view, i.e., 4-fold coverage. However, not every constellation we use in our comparison is PNT focused, and may not be optimized for 4-fold coverage. Thus, we compute both 4-fold and 1-fold coverage: the coverage here is computed as the percentage of the number of users that have at least 4 and 1 satellites in view, respectively. The GDOP and PDOP are DOP metrics that reflect the geometry of the user and the constellation [ 37]; the PDOP reflects the 3D position accuracy and the GDOP reflects the joint 3D position-and-timing accuracy. Similarly, the /0 reflects the quality of the received signal, and it is calculated via eq. (1), where is the bandwidth of the channel, and Signal-to-Noise Ratio (SNR) is calculated for each satellite-user pair.
/0− = + 1010() (1) A high PNT performance with respect to these metrics is reached for high 4-fold coverage, low values for DOP metrics, and high values for /0.
In our previous works [
(ℎ) = 286.8374 − 4.7805ℎ − 0.1402ℎ2 [] (ℎ) = 1008.0278 − 113.2494ℎ + 3.9408ℎ2 [ℎ ] (ℎ) = 8.988 exp(− 03614ℎ − 0.005402ℎ2 − 0.001955ℎ3) [/3] (2) (3) (4)
i In Table 3, the cases with 0% 4-fold coverage show the GDOP, PDOP, /0 and the received power values as N/A, meaning not applicable, as DOP metrics have no physical meaning outside of instances where PNT solutions exist. ii In instances where the coverage does not change between Tables 2 and 3, the average /0 and received power values are the same (i.e., Starlink O-2), but for instances that change (i.e., Starlink O-1), the better coverage instances include more conditions with weak signals, thus both the average /0 and received power values decrease. iii It can be seen from Table 3 that Starlink, Xona and Centispace are the constellations that provide resilience to indoor and low sensitivity conditions, and are still able to provide acceptable DOP metrics given the four-fold coverage is achieved. In the less challenging scenarios (O-2, O-3 and O-4), every LEO constellation is able to achieve acceptable metrics in low sensitivity conditions, with Starlink, OneWeb and Xona being able to achieve full coverage. In comparison, Galileo is able to either operate fully, as seen in O-2 and O-3 scenarios, or not able to operate at all due to the low sensitivity of the receivers. iv Table 2 shows a diferent picture, that even in high-sensitivity conditions, it can be challenging to achieve a four-fold coverage. Centispace and the experimental designs show a similar picture; they are able to achieve acceptable LEO-PNT metrics with a relatively low number of LEO satellites, yet they struggle to achieve a complete four-fold coverage; while Xona’s design seems to be better performing but still cannot guarantee complete four-fold coverage in all scenarios. Among the mega-constellations, Starlink and OneWeb achieve the best performance and are very similar, with Kuiper falling behind; providing a better LEO-PNT performance compared to the smaller LEO constellations, but failing to achieve a complete four-fold coverage in any scenario. Comparing the rest of Table 2 to the Galileo entry, which serves as the GNSS benchmark, it is clear that similar, if not better, PNT performance can be achieved with the considered LEO constellation designs in comparison.
Galileo values serve as a benchmark and show what metrics are obtained with the current GNSS systems in the considered scenarios, as well as what potential a LEO-PNT constellation has. Values in Table 2 in particular, as the sensitivity allows for very high coverage for almost all designs, show what the main appeal of a dedicated LEO-PNT constellation is over the GNSS constellations; a significant improvement in /0 for the same frequency band, and therefore, the possibility of shifting operations to higher frequency bands, which are less crowded. While the best performing LEO constellation in this study is indeed Starlink, we would like to emphasize that this does not strictly mean that a mega-constellation is necessary to achieve good LEO-PNT services. In fact, the four-fold coverage diference seen between Kuiper, Xona and Centispace shows that simply increasing the number of satellites within a constellation does not directly translate into improved PNT performance. The smaller scale LEO-PNT constellations and the author team’s experimental designs provide a more balanced approach between cost/complexity of the constellation and its PNT performance. Their /0 is a direct improvement compared to Galileo, and the DOP metrics, while slightly worse, are still within the same performance range of < 10.
We would like to further demonstrate two aspects via Fig. 1. The first aspect is that, Similar trends are seen for both I-1 and O-2 scenarios. Indoor and outdoor conditions afect the constellations in the same way by lowering their /0 values drastically; which can impact the coverage depending on receiver sensitivity levels. Fig. 1a and 1b show the LEO-PNT metrics of the considered constellations with respect to each other for the high-sensitivity case, for two selected scenarios; I-1 and O-2. Looking at Fig. 1a and 1b, Starlink and Oneweb yields drastically better /0 and GDOP than Galileo while equally maintaining the complete coverage, and Kuiper showing slightly worse /0 and GDOP compared to the other mega-constellations, yet fails to keep up with the complete coverage provided by Galileo. Aside from the mega-constellations, Xona, Centispace and the experimental designs also provide /0 improvements over Galileo. Xona yields a slight improvement with respect to the GDOP, while Centispace and the experimental designs have slightly worse GDOP compared to Galileo, but still remain within good GDOP value ranges. We can also see that the average number of visible satellites are higher compared to Galileo for the mega-constellations, Xona, and the experimental designs, which (a) I-1 for -185 dBm
(c) GDOP in I-1 for -185 dBm (b) O-2 for -185 dBm (d) /0 in I-1 for -185 dBm imply better stability in cases of satellite failures.
The second aspect is the carrier frequency efect on LEO-PNT. Fig. 1c and 1d presents GDOP and /0 respectively for a subset of four constellations; Galileo, Oneweb, Centispace, and Experimental 1; representing the GNSS benchmark, mega-constellations, small-scale LEO constellations, and potential LEO-PNT constellations respectively. Scenario I-1 is shown as an example, with the observation that similar trends have been noticed for O-2 scenario as well. The GDOP is not influenced much by the carrier frequency, with the exception of Galileo, whose signals fail to penetrate the indoor scenario with enough strength to be received by the receiver after around 20 GHz. On the other hand, /0 drops in a consistent manner as for all constellations as the carrier frequency increases. Together, this shows us that going above X-band or Ku-band for the carrier frequency would risk operational failure for GNSS systems, while LEO-PNT systems would be able to support up to Ka-band carrier frequencies. We note that LEO constellations operating in K-band can reach to the same /0 values that the GNSS constellations have in L-band, and that if the same carrier frequency is used, the improvement is significant in favor of the LEO constellations versus Galileo, and GNSS by extension.
This article has shown an extensive comparison between seven LEO satellite constellations and Galileo constellation as the GNSS benchmark (provided in Table 1) in terms of LEO-PNT metrics. We selected the coverage, the GDOP, and the /0 as relevant LEO-PNT performance metrics to be in used comparisons. Using a MATLAB simulation created in-house for analysis, Tables 2 and 3 detail the impact of diferent scenarios and receiver sensitivities on these performance metrics. Indoor/outdoor, rural/urban, and LOS/NLOS scenarios are considered in the link budget, and compared for low (i.e., -125 dBm) versus high (i.e., -185 dBm) receiver sensitivity cases. We show that, among the available and upcoming LEO constellations, Starlink, OneWeb, and Xona are the most promising for future LEO-PNT applications. We also show that experimental designs that can reach similar GDOP and coverage performance as Galileo (and GNSS by extension) are possible, which provide a direct improvement on /0. This fact also hints at the possibility that alternative LEO-PNT constellation designs can be further optimized for even better LEO-PNT solutions.
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