Methods and devices for GNSS signal processing

Abstract

Method for processing a group of GNSS signal data derived from observations of GNSS signals from multiple transmitters over multiple epochs, wherein the GNSS signals have a first signal and a second signal on a first band that can be tracked as a single broadband signal and of which each can be tracked separately, comprising the following steps: a. Obtaining carrier phase observations of the first signal, b. Obtaining carrier phase observations of the second signal, c. Obtaining code observations of the broadband signal, and d. Estimating values ​​for a parameter group comprising the following from a group of observables that includes the carrier phase observations of the first signal, the carrier phase observations of the second signal, and the code observations of the broadband signal: the position of a receiver of the GNSS signals, the clock error of a receiver of the GNSS signals, and an array of ambiguities that includes an ambiguity for each transmitter from which carrier phase observations of the first signal are obtained, and an ambiguity for each transmitter from which carrier phase observations of the second signal are obtained.

Description

TITLE OF THE INVENTION METHODS AND DEVICES FOR GNSS SIGNAL PROCESSING FIELD OF THE INVENTION

[0001] The present invention relates to the field of global navigation satellite systems. More specifically, the present invention relates to methods and apparatus for processing signals from GNSS satellites with multiple signals on a single band that can be tracked together or separately. GENERAL STATE OF THE ART

[0002] Global Navigation Satellite Systems (GNSS) include the Global Positioning System (GPS), the GLONASS system, the proposed Galileo system, and the proposed Beidou (Compass) system.

[0003] The Global Positioning System realized its original design goals when it reached full operational capability in 1995. Technical advances and new system requirements have since led to modernization efforts. The GPS Modernization Project involves new ground stations and new satellites with additional navigation signals and improved accuracy and availability. The first GPS satellite with triple-frequency capability, including the new L5 frequency, GPS Block IIF-1, is expected to be launched in the summer of 2009. The new L5 signal for civil use is expected to improve the signal structure for better performance, with greater transmit power and wider bandwidth than the L1 and L2C signals, to handle interference better than with L2.The launch of additional three-frequency GPS satellites is planned, although a complete three-frequency constellation will likely not be available for another five to seven years. Each GPS signal is modulated on a separate carrier and thus individually tracked by a receiver. The GPS system is designed to accommodate two levels of service: civil and military.

[0004] The European Galileo satellite system will have similar capabilities, but may not make all of them available for free broadcast. The Galileo launch program is behind schedule. So far, only the two Galileo Validation Element satellites, GIOVE-A and GIOVE-B, have been launched. A key difference from the GPS system is that the Galileo system's signal structure is planned to feature ten different signals transmitted on four frequency bands to accommodate four service levels. The Galileo signals E1 and E2 are on separate carriers in the E2-L1-E1 band (sometimes referred to as the L1 band).The Galileo E1 signal has a wider signal frequency range than the GPS L1-C / A signal, so a simple receiver processing the main lobe of the Galileo E1 Open Service (OS) signal will consume more power than its equivalent processing the main lobe of the GPS C / A signal. The Galileo E6 signal is on a separate carrier in the E6 band, which carries the Commercial Service (CS) and Public Regulated Service (PRS) signals. In contrast, the Galileo E5a and E5b signals are on a single carrier in the L5-E5a-E5b band. The E5a and E5b signals [have] two spectral components generated by a single modulation called Alternative Binary Offset-Carrier (AltBOC) modulation. The AltBOC modulation provides a constant envelope and allows receivers to distinguish between the two spectral lobes.AltBOC modulation enables coherent tracking of the entire E5a+E5b signal as a single broadband signal, or non-coherent tracking of each of the E5a and E5b signals separately. The E5a and E5b signals are available for Open Service (OS), Commercial Service (CS), and Safety of Life (SOL) services.

[0005] The Galileo system is the only system currently proposed to transmit a signal on a single band, with a first signal and a second signal that can be tracked as a single broadband signal or tracked separately. The Chinese Compass system is in its early stages of testing, and its signal structure is subject to change. The Russian GLONASS system is expected to have additional frequency capabilities at a later date, and its signal structure is also subject to change. India is also planning a GNSS system.

[0006] US 20090027264 A1 describes GNSS signal processing using an ionosphere-free geometry filter. Data from a network of GNSS reference stations are processed. The ionosphere-free geometry filter allows processing time to evolve more linearly with the number of reference stations.

[0007] DE000060318125T2 describes a GNSS receiver for Galileo AltBOC satellite signals. A controller compares a local composite code with a received AltBOC composite code based on a correlation signal. The controller includes means for determining a global position based on timing differences.

[0008] US020070201537A1 describes a method for demodulating a Galileo Alternative Binary Offset Carrier signal. The signal is converted to an intermediate frequency, filtered, and sampled. For each subcarrier, pseudorandom binary codes and a subcarrier phase are generated, which are used to correlate the sampled signal.

[0009] US020050270997A1 describes a BOC signal detection and tracking method. The method includes a code delay detector provided by combining a BOC autocorrelation function and a BOC / PRN cross-correlation function.

[0010] WO002008017860A1 describes a receiver for signals modulated by BOC. A subcarrier phase and a code phase are tracked independently and interactively.

[0011] US020050101248A1 describes a method for processing GNSS signals using geometry filters and ionospheric filters. A first multi-carrier GNSS and a second multi-carrier GNSS are used. Ambiguity estimates are performed independently for the two GNSS systems in separate signal paths and then combined.

[0012] Improved methods and apparatus for processing GNSS signals are desired, particularly to improve the ambiguity estimation of GNSS signals that have a first signal and a second signal on a band and that can be tracked as a single broadband signal or separately. SUMMARY OF THE INVENTION

[0013] The improvement is achieved by the subject matter of the independent patent claims. Advantageous embodiments are set forth in the dependent patent claims.

[0014] The methods and apparatus according to examples provide improved processing of GNSS signals having a first signal and a second signal on a first band that can be tracked as a single broadband signal and each of which can be tracked separately.

[0015] Some examples provide improved ambiguity estimation of such GNSS signals alone. Other examples provide improved ambiguity estimation of such GNSS signals together with other GNSS signals on one or more other bands.

[0016] According to some examples, methods are provided for processing a group of GNSS signal data derived from observations of GNSS signals from multiple transmitters over multiple epochs, the GNSS signals comprising a first signal and a second signal on a first band that can be tracked as a single broadband signal and each of which can be tracked separately, comprising the steps of: obtaining carrier phase observations of the first signal, obtaining carrier phase observations of the second signal, obtainingObtaining code observations of the broadband signal and estimating, from a set of observables comprising the carrier phase observations of the first signal, the carrier phase observations of the second signal and the code observations of the broadband signal, values ​​for a set of parameters comprising: the position of a receiver of the GNSS signals, the clock error of a receiver of the GNSS signals and an array of ambiguities comprising an ambiguity for each transmitter from which the carrier phase observations of the first signal are obtained and an ambiguity for each transmitter from which the carrier phase observations of the second signal are obtained.

[0017] According to some examples, the first signal and the second signal are respective spectral components of a single alternative binary offset modulation. According to some examples, the first band is the Galileo E5 band, the only wideband signal is the Galileo E5ab signal, the first signal is the Galileo E5a signal, and the second signal is the Galileo Eb5 signal.

[0018] According to some examples, the GNSS signals comprise a third signal on a second band, the method further comprising obtaining carrier phase observations of the third signal, the set of observables further comprising the carrier phase observations of the third signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the third signal are obtained. According to some examples, the second band is the Galileo E2-L1-E11 band, and the third signal is the Galileo E1 signal.

[0019] Some examples further include obtaining carrier phase observations of the wideband signal, wherein the set of observables further comprises the carrier phase observations of the wideband signal, and wherein the array of ambiguities further comprises an ambiguity for each transmitter from which carrier phase observations of the wideband signal are obtained.

[0020] According to some examples, the GNSS signals comprise a fourth signal on a third band, the method further comprising obtaining carrier phase observations of the fourth signal, the set of observables further comprising the carrier phase observations of the fourth signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the fourth signal are obtained. According to some examples, the third band is the Galileo E6 band and the fourth signal is the Galileo E6 signal.

[0021] Some examples further include obtaining code observations of the first signal, and the set of observables further includes the code observations of the first signal. Some examples further include obtaining code observations of the second signal, wherein the set of observables further includes the code observations of the second signal. Some examples further include obtaining code observations of the third signal, wherein the set of observables further includes the code observations of the third signal. Some examples further include obtaining code observations of the fourth signal, wherein the set of observables further includes the code observations of the fourth signal.

[0022] According to some examples, estimating the set of parameters comprises applying to the set of observations a filter having a plurality of states corresponding to parameters of the parameter set.

[0023] According to some examples, estimating the parameter set comprises the following steps: applying to the set of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; applying to the set of GNSS signal data a bank of geometry-free filters that use geometry-free combinations to obtain an array of ambiguity estimates for the geometry-free combinations and associated statistical information;and combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the geometry-free carrier phase combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information;

[0024] According to some examples, estimating the parameter group comprises the steps of: applying to the group of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; applying to the group of GNSS signal data a bank of ionospheric filters that use a geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; applying to the group of GNSS signal data at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information;and combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information;

[0025] According to some examples, estimating the parameter set comprises the steps of: applying to the set of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; applying to the set of GNSS signal data a bank of ionospheric filters that use a geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information;Applying to the group of GNSS signal data at least one bank of additional (also called quintessence or "Q") filters that use a geometry-free and ionosphere-free carrier phase combination to obtain an array of ambiguity estimates for the geometry-free and ionosphere-free carrier phase combination and associated statistical information; Applying to the group of GNSS signal data at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information;and combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information, and the array of ambiguity estimates for the geometry-free and ionospheric-free carrier phase combination and associated statistical information, and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information;

[0026] According to some examples, the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating-point value, and the method further includes reporting the estimated position of the receiver. Some examples further include defining at least a subset of the array of ambiguities as integer values ​​and reporting the estimated position of the receiver. Some examples include assigning integer values ​​to at least a subset of the array of ambiguities to define a plurality of candidate groups; determining a quality measure for each of the candidate groups; and obtaining a weighted average of at least a subset of the candidate groups, wherein each candidate group of the weighted average is weighted based on its quality measure.

[0027] Some examples further include applying corrections to the observations before estimating the set of parameters from the set of observables.

[0028] According to some examples, the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, and the corrections comprise observations of GNSS signals acquired at a reference receiver, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with the observations acquired at the reference receiver to achieve differential observations, wherein estimating values ​​for the parameter group comprises estimating the values ​​from the differential observations, and wherein estimating values ​​for the parameter group comprises estimating a position of the reconnaissance element receiver.

[0029] According to some examples, the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, and the corrections are derived from observations of GNSS signals acquired at a plurality of reference receivers, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with the virtual reference station data to achieve network-corrected observations, wherein estimating values ​​for the parameter group comprises estimating the values ​​from the network-corrected observations, and wherein estimating values ​​for the parameter group comprises estimating a position of the reconnaissance element receiver.

[0030] According to some examples, the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, wherein the corrections comprise satellite orbit data and satellite clock data, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with the satellite orbit data and the satellite clock data to obtain corrected observations, wherein estimating values ​​for the parameter group comprises estimating the values ​​from the corrected observations, and wherein estimating values ​​for the parameter group comprises estimating a position of the reconnaissance element receiver.

[0031] According to some examples, estimating values ​​for the parameter group is performed essentially in real time (e.g., a few seconds after the GNSS signal observations are acquired). According to some examples, estimating values ​​for the parameter group is performed in a post-processing operation that is essentially not real time (e.g., in a post-processing operation performed on previously recorded observations).

[0032] According to some examples, devices are provided to perform the methods summarized above. According to some examples, a reconnaissance element receiver is provided that includes such devices. According to some examples, a network station is provided that includes such devices. According to some examples, a computer program is provided that includes instructions configured to perform one or more of the methods summarized above when executed on a computer processing device. According to some examples, a computer-readable medium is provided that includes a computer program that includes instructions configured to perform one or more of the methods summarized above when executed on a computer processing device. SHORT DESCRIPTION OF THE DRAWING

[0033] These and other aspects and features of the present invention will become more clearly understood from the embodiments described below with reference to the drawing figures. Fig. 1 schematically illustrates a positioning scenario using a GNSS sensing element receiver capable of receiving GNSS signals comprising a first signal and a second signal on a first band, tracked as a single broadband signal, each of which is tracked separately. Fig. 2 is a block diagram of an integrated GNSS receiver system capable of receiving GNSS signals comprising a first signal and a second signal on a first band, tracked as a single broadband signal, each of which is tracked separately. Fig. 3 schematically shows the signal structures within the bands of existing GNSS systems. Fig. 4 schematically illustrates a GNSS signal processing flow according to some embodiments of the invention. Fig. 5 schematically shows a filter architecture according to some embodiments of the invention. Fig. 6 schematically illustrates a process flow according to some embodiments of the invention. Fig. 7 schematically shows a filter architecture according to some embodiments of the invention. Fig. 8 schematically shows a process flow according to some embodiments of the invention. Fig. 9 schematically shows a filter architecture according to some embodiments of the invention. DETAILED DESCRIPTION

[0034] Embodiments of the invention generally relate to any GNSS having a first signal and a second signal on a first band that can be tracked as a single broadband signal and each of which can be tracked separately.

[0035] The Galileo signal structure includes the L1, E5a / E5b, and E6 bands. The E6 band is a publicly regulated signal and is therefore unlikely to be available for general use. The E5a and E5b signals can be tracked together as a single broadband signal, and each can also be tracked separately. The Chinese Beidou (Compass) satellite system is already under development, but no details of the final signal structure are known. Further individual units of existing and planned GNSS signal spectra can be found in S. Lo et al., 2006, "GNSS Album - Images and Spectral Signatures of the New GNSS Signals," INSIDE GNSS, May / June 2008, pp. 46-56.

[0036] Various methods and apparatus are described for processing GNSS signal data derived from observations of GNSS signals comprising a first signal and a second signal on a first band, which can be tracked as a single broadband signal, and each of which can be tracked separately. The GNSS signals may also further comprise at least one of a third signal on a second band and a fourth signal on a third band. The GNSS signal data comprises at least carrier phase observations for the first signal and the second signal, and code (pseudo-range) observations for the broadband signal. The GNSS signal data may further comprise carrier phase observations and / or code (pseudo-range) observations for any or all of the signals, as will be described.

[0037] For illustrative purposes, we assume that the satellite system used is Galileo. Thus, the following examples denote the first signal by E5a, the second signal by E5b, the broadband signal by E5ab, the third signal by E1, and the fourth signal by E6. The proposed approaches can be readily applied to signals from other GNSS satellite systems and pseudolites without losing generality, provided that the signal structure comprises a first signal and a second signal on a first band, which can be tracked as a single broadband signal, and each of which can be tracked separately.

[0038] There are several options for tracking the Galileo ES frequency: E5a, E5b, and E5ab-AltBOC. The E5ab modulation method offers a primary advantage at the pseudorange error level when tracking the E5ab code, although tracking the E5a and E5b signals separately enables dual-frequency, triple-frequency, or even quadruple-frequency carrier-phase ambiguity resolution, with all its reliability and performance benefits, without having to track the proprietary and easily blocked E6 signal. Tracking the E6 signal further enables quintuple-frequency carrier-phase ambiguity resolution.

[0039] Assuming that the center frequencies of E5a and E5b are sufficiently separated to achieve a significantly different multipath error, E5a and E5b represent the optimal choice for carrier-phase observations. Due to its advantages for code tracking, E5ab is the best choice for tracking the ES pseudopaths. Furthermore, if E5ab—centered around the E5 frequency—is uncorrelated with E5a and E5b with respect to multipath error, then quadruple-frequency ambiguity resolution is better than triple-frequency. The same applies to the "redundant" use of all three codes on E5: E5a / E5b and E5ab.

[0040] This approach is also applicable to any other GNSS signal that provides the ability to track different carrier signals at a frequency other than the center frequency.

[0041] For Galileo signals, the use of E1 / E5a / E5b or E1 / E5 / E6 carrier phase observations for triple-frequency ambiguity resolution and E1 / E5ab carrier phase observations for double-frequency ambiguity resolution is known.

[0042] To date, the use of E5a / E5b carriers plus E5ab code (pseudo-range) observations has not been proposed, nor has the use of E1 / E5a / E5b carrier-phase observations plus E1 / E5ab code (pseudo-range) observations. Nor has the use of E1 / E5a / E5b / E5ab carrier-phase observations for quadruple-frequency ambiguity resolution been proposed.

[0043] In principle, any combination of carrier phase and code (pseudo-range) observation data can be used for ambiguity resolution. The observables generally obey the standard observation equations, and these are linearly combinable.

[0044] The use of three or more carriers has been shown to improve the reliability and / or convergence times of GNSS ambiguity resolution methods.

[0045] Trimble's recently launched R8 GNSS system is a Galileo-capable, multi-channel GNSS receiver system that enables simultaneous tracking of E1, E5a, E5b, and E5ab-AltBOC. Currently, the signals transmitted by the experimental test satellites Galileo GIOVE-A and GIOVE-B can be tracked for evaluation and testing purposes.

[0046] If significant correlations exist between the different ES carriers and / or codes, this can be properly modeled in the calculation of the floating-point solution.

[0047] In general, the use of the E5ab-AltBOC pseudorange data is optimal directly, i.e. not in a combination of observables with other pseudoranges from other frequency modulations.

[0048] A conventional floating-point formulation according to some embodiments of the invention uses at least the code (pseudo-range) observations from E5ab-AltBOC together with carrier phase observations from E5a and E5b for double-frequency ambiguity resolution. Some embodiments of the invention also use E1 carrier phase observations for triple-frequency ambiguity resolution. Some embodiments of the invention also use E5ab carrier phase observations for quadruple-frequency ambiguity resolution. Some embodiments of the invention further use E6 carrier phase observations for quintuple-frequency ambiguity resolution. Some embodiments of the invention further use the E1 code observations and / or the E5a code observations and / or the E5b code observations and / or the E6 code observations.

[0049] Some embodiments employ a conventional formulation of a floating-point solution for quadruple-frequency ambiguity resolution using code (pseudo-range) observations of at least the E5ab-AltBOC signal plus (optionally) any combination of E1, E5a, and E5b code (pseudo-range) observations together with carrier phase observations of the E5a and E5b signals and optionally the E1 signal or the E1 and E5ab signals or the E1 and E5ab and E6 signals.

[0050] Some embodiments use a factorized multi-carrier translation as described in U. Vollath, "The Factorized Multi-Carrier Ambiguity Resolution (FAMCAR) Approach for Efficient Carrier-Phase Ambiguity Estimation," ION GNSS 17th International Technical Meeting of the Satellite Division, September 21-24, 2004, Long Beach, CA, pp. 2499-2508, and in US Patent US 7,432,853 B2. In a FAMCAR formulation, some embodiments use E5ab-AltBOC filters without a carrier code for each Galileo satellite. In some embodiments, the ionospheric filters use any combination of carrier phase observations of signals E5a and E5b, or signals E1 and E5b, or signals E1 and E5a, or signals E1 and E5b. In some embodiments, the additional filter (also referred to as a "quintessence" or "Q" filter) uses carrier phase data from signals E1, E5a, and E5b.

[0051] For quadruple-frequency ambiguity resolution, some embodiments of the FAMCAR implementation use code filters that use a combination of carrier-less E5ab AltBOC code for each Galileo satellite. In some embodiments, the ionospheric filters use combinations of carrier-phase observations of signals E5a and E5b, or signals E1 and E5a, or signals E1 and E5b, or signals E1 and E5a and signals E1 and E5b. In some embodiments, the additional filters (also referred to as "quintessence" or "Q" filters) use carrier-phase observations of signals E1, E5a, E5b, and E5ab.

[0052] The following table summarizes the Galileo signal observables used in some embodiments. Entries marked with "X" indicate the use of the observation; entries marked with "-" indicate no use of the observation; entries marked with "O" indicate the optional use of the observation. TABLE I Description Carrier phase observations Code (pseudo-route) observations E1 E5a E5b E5ab E6 E1 E5a E5b E5ab E6 Dual frequency (cost-effective receiver) - X X - - - - - X - Triple frequency (single code) X X X - - - - - X - Triple frequency (multi-code options) X X X - - O O O X - Quadruple frequency (single code) X X X X - - - - X - Quad frequency (multi-code options) X X X X - O O O X - Quintuple frequency (single code) X X X X X - - - X - Five-fold frequency (multi-code options) X X X X X O O O X O

[0053] The Galileo signal E5ab-AltBOC is particularly interesting for code observations due to its relatively low noise. The ability to acquire these observations is supported by Trimble's recently introduced R8 GNSS system. Tracking the E5ab-AltBOC signal provides robust code (pseudorange) tracking with range errors in the range of 5 to 10 cm. Other GNSS signals typically lie closer to the 20 to 30 cm range. Combining E5ab code observations with carrier-phase observations of E5a, E5b, or E1 is expected to result in good pseudoranges.

[0054] Combining E5ab code observations with carrier phase observations from E5a and E5b provides a three-frequency process that can be implemented in a low-cost single-band receiver because the radio frequency and other hardware and power requirements are much lower than for a receiver with multi-band capability.

[0055] Noise considerations play a role in the rational selection of observations to be used. For example, the E5b signal is approximately 2 to 3 times noisier than the E5ab signal. Averaging the observations of the E5a and E5b signals would only take the average of the noise from the two signals, and this would be expected to reduce the pseudorange error by approximately 30%. In contrast, observations of the E5ab-AltBOC signal reduce the deviation by a factor of 2 or 3. Good (low-noise) pseudorange observations are important because they drive the convergence of the carrier phase ambiguity estimate. Thus, the E5ab signal is a good choice for code (pseudorange) observations.

[0056] However, for ambiguity resolution, it is helpful to use as many carriers as possible. For more information on ambiguity resolution with multiple carriers, see, for example, US Patent No. 7,432,853 B2. It is therefore desirable to use the carrier phase observables from E5a and E5b, as well as all available carrier phase observables from E1, E5ab, and E6. Using all available code observations from signals E1, E5a, E5b, and E6 is also helpful. Many of the variations are covered in Table I above.

[0057] From a resource perspective (e.g., receiver hardware, processing capacity, power consumption), it is prudent to select subsets of signal observations that provide the greatest value for the resources used. Some of the possible observations do not contribute much value. Signals only add value as multiple signals if they are coherent signals from the same satellite. For carrier-phase observations, multipath error is the most significant problem, so using carrier-phase observations of the E5ab signal together with carrier-phase observations of the E5a and E5b signals is not very advantageous.

[0058] Conventional filtering of GNSS observations uses the well-known floating-point solution. The code (pseudorange) observations are defined as follows: ρLi,rKis=Rrs+Trrs+cΔtr−cΔts+λLi2λL12Irs and the carrier phase observations are defined as follows: φLi,rPjs=1λLi(R+Tr+cΔt−cΔt+λLi2λL12Irs)+NLi,rs where is the code observation of a signal L from a satellite s at a receiver r, L i ∈ {L1, L2, L5, E1, E5a, E5b, ESab} is the group of possible signals, e.g. GPS L1, L2 and L5 and Galileo E1, E5a, E5b and E5ab, K i ∈ {L1, L2, L5, E1, E5a, E5b, E5ab} is a reasonable selection of code observations, p j ∈ {L1, L2, L5, E1, E5a, E5b, E5ab} is a reasonable selection of carrier phase observations, r is the receiver who records the observation, s is the satellite (transmitter) from whose signal the observation is recorded. Tr is a parameter (filter state) for the troposphere, I r is a parameter (filter state) for the ionosphere that affects the observation at the receiver r, c is the speed of light in a vacuum, tr is a parameter (filter state) for the receiver clock, t s is a parameter (filter state) for the satellite clock, λ Li the wavelength of the signal L i is, the ambiguity in the carrier phase observation of the signal L i from the satellite s at the receiver r.

[0059] In general, it is desirable to select the smallest group of observations that yields good performance. It is also desirable to select as many carrier-phase observations as possible, not necessarily matching the code observations. The number of carrier-phase observations is important for determining carrier-phase ambiguities, whereas for code observations, the quality of the code observations is most important. Thus, it is desirable to start with less noisy code observations and use multi-frequency carrier-phase observations for ionospheric attenuation and ambiguity estimation. The carrier-phase observations help mitigate multipath error, so the ionospheric information is less noisy.For example, it is desirable to use carriers that are as far apart in frequency as possible, the farther the better, recognizing that they are most valuable along long baselines (between reconnaissance element and reference receiver in differential mode) and for precise point location with a single receiver.

[0060] To mitigate multipath error, it is helpful if the carrier phase observations are of similar quality. By weighting each of them with the sigma of the other σ22ρ1+σ12ρ2σ12+σ22 The optimum (minimum noise) is achieved when the sigma is approximately equal to: σ2≡1=12(ρ1+ρ2)

[0061] For example, using carrier-phase observations of E5ab and E1, where the noise of the E5ab observation is about three times as strong as the noise of the E1 observation: 32ρE5ab+12ρE132+12=910ρE5ab+110ρE1 Thus, combining the carrier-phase observations of a "bad" signal with those of a "good" signal is not very helpful and is reflected in the final accuracy. Using E1 carrier-phase observations with E5ab carrier-phase observations is only slightly better than using only E5ab carrier-phase observations.

[0062] It is also useful to consider the value of using code (pseudo-range) observations from two signals when attempting to model the ionosphere from the code observations ρ of signals 1 and 2: I=(ρ2−ρ1)(λ12λ22−λ12) where (λ12λ22−λ12) is the normalization factor of the ionosphere (wavelength), which converts the ionospheric information back into the first fundamental oscillation.

[0063] If one renormalizes back to the ionosphere, because the observations are frequency dependent, when λ1 and λ2 are close to each other and have the same σ, then: σ(I)=2∂ρ(λ12λ22−λ12)≈2−3

[0064] Thus, the ionospheric information is very noisy compared to the individual pseudoranges used and thus provides very little information when the frequencies are close to each other.

[0065] The situation is better when the frequencies are far apart: σ12+σ22(λ12λ22−λ12) where σ12+σ22 dominated by the “worst” code observation.

[0066] Thus, the result of averaging code (pseudo-range) observations of two signals is better than, but close to, the worst of the two observations, but for the ionosphere the result is worse than the worst of the two observations.

[0067] There are several reasons why it is more desirable to have carrier phase observations from multiple signals than code (pseudo-range) observations from multiple signals: • The error propagation of carrier phase observations is comparable to that of code observations. • The carrier phase observations are of approximately the same quality, resulting in approximately the same quality when averaged, in contrast to code observations, which are of different quality and resulting in a quality closer to the worst of the two observations when averaged. • The final phase accuracy is crucial for ambiguity resolution. ◯ The accuracy of estimating the receiver position with the ambiguity estimates of the floating-point solution is not as good as with properly fixed ambiguity values ​​or with a weighted average of integer ambiguity candidate groups. ◯ The ionospheric information for each correct integer ambiguity candidate is on the order of 1 cm. • The ambiguities for all carriers must be the same (except ionosphere). ◯ When integer ambiguity candidate groups are formed, they sometimes do not agree.

[0068] These considerations illustrate why it is desirable to optimize the selection of signals for which code observations and carrier phase observations are used in the estimation process. In summary, for code filters, the quality of the best code observation is crucial, whereas for ionospheric filters, the quality of the worst code observation is crucial.

[0069] Comparatively, the noise factor for the GPS code L1 / L2 is σ(I) 2.2, thus 2 better, and the overall factor is 3.

[0070] US Patent No. 7,432,853 B2 also describes FAMCAR methods for carrier ambiguity estimation at two or three or more frequencies, and for non-uniform carrier ambiguity estimation at two frequencies and three or more frequencies. Ionospheric filters form an important part of the FAMCAR estimation method for ambiguity estimation at two or more frequencies. On short baselines, the ionospheric influence is tightly confined, and this information helps to integrate the ambiguity estimation of the carrier frequency observations used in the filters. The additional (also called "quintessence" or "Q") filters do not contribute the same level of information as the ionospheric filters.On long baselines, where the ionospheric influence is not so well known, the ionospheric filters still provide a useful constraint on the relationship between the ambiguities of the carrier frequency observations. Constraining the ionospheric influence is important for successful integer carrier phase ambiguity resolution. When the GNSS signal carriers are derived contiguously from the same fundamental frequency reference on the satellite, an intrinsic relationship exists between the carrier ambiguities. This relationship leads to a search space in which the coincidence of the carrier wavefronts occurs only on certain harmonics of the carrier frequencies.

[0071] According to some embodiments of the invention, an additional filter (also called a "quintessence" or "Q" filter) is added to model the third and subsequent carriers for each satellite.

[0072] According to some embodiments, an auxiliary code filter using a code-carrier combination is added to utilize the code observation on a third frequency, e.g., E1, E5a, or E5b, to improve the estimation process.

[0073] The selection of the observation type for the third frequency is important. According to some embodiments of the invention, the three-frequency ionospheric filters use a geometry-free, best-effect ionospheric combination. According to some embodiments of the invention, the additional filters (also called "quintessence" or "Q" filters) use three frequencies to use a geometry-free, ionospheric-free phase combination. According to some embodiments of the invention, the code-carrier combination of the auxiliary code filters uses the third-frequency code observation (e.g., E5a or E5b, where the first and second frequency code observations are E5ab and E1) with a three-frequency carrier-phase combination (e.g., a combination of carrier-phase observations for E5ab / E1 / E5a ​​or E5ab / E1 / E5b) that has an ionospheric influence identical to the ionospheric influence of the code observation (e.g.,a carrier phase combination for E5ab / E1 / E5a ​​or E5ab / E1 / E5b with an ionospheric influence that matches the ionospheric influence of the code observation for E5a or E5b, respectively).

[0074] Fig. Figure 1 schematically depicts a positioning scenario 100 using a GNSS receiver 105 capable of receiving a first signal (e.g., Galileo E5a) and a second signal (e.g., Galileo E5b) on a first band (e.g., Galileo E5), which can be tracked as a single broadband signal (e.g., Galileo ESab-AltBOC), and each of which can be tracked separately. Each of the signals is tracked by the receiver 105 for each of the visible GNSS satellites, such as GNSS satellites 110, 120, 130. The signals are affected by the Earth's atmosphere 140 (in particular, the ionosphere and troposphere) and by multipath, as schematically depicted at 150. Fig.1 also shows an optional correction source for supplying optional correction data 170 for use in processing observations of the satellite signals acquired at the receiver 105.

[0075] Fig.Figure 2 is a block diagram of a typical integrated GNSS receiver system 200 including a GNSS antenna 205 and communications antennas 210. The Trimble R8 GNSS system is an example of such a system. The receiver system 200 may serve as a reconnaissance element or a base station or reference station. The receiver system 200 includes a GNSS receiver 215, a computer system 220, and one or more communications links 225. The computer system 220 includes one or more processors 230, one or more data storage elements 235, program code 240 with instructions for controlling the processor(s) 230, and user input / output devices 245, which include one or more output devices 250, such as a display, speaker, or printer, and one or more devices 255 for receiving user input, such as a keyboard, touchpad, mouse, or microphone.

[0076] Fig.Figure 4 schematically shows the lower L-band and upper L-band regions of the spectrum, where the GPS, GLONASS, and Galileo signals are located. The lower L-band contains the signals from GPS L5, Galileo E5a, E5b, and E5ab. The middle L-band contains the signals from GPS L2 and GLONASS G2. The upper L-band contains the signal from Galileo E6. The lower L-band contains the signals from GPS L1, Galileo L1, Galileo E2, and Galileo E1. The upper L-band contains the signal from GLONASS G1.

[0077] Fig.Figure 4 schematically depicts a high-level GNSS signal processing flow 400 according to some embodiments of the invention. A GNSS signal data group 405 is a group of observations obtained by receiving signals from multiple satellites at a receiver. The GNSS signal data group 405 is optionally prepared for subsequent filtering at 410. The resulting prepared data 415 includes code (pseudorange) observations and carrier phase observations of GNSS signals, as previously described.

[0078] According to some embodiments, data preparation 410 requires some or all of the following steps: (1) storing (caching) GNSS observation data of a reconnaissance element epoch, (2) temporal synchronization of the GNSS observation data between the reference and reconnaissance element epochs after the reference data has been received, (3) applying antenna correction models to observations from the base and reconnaissance element, (4) optionally forming pseudorange and carrier phase observations for each GNSS frequency band with a single difference (between base and reconnaissance element), (5) optionally applying tropospheric correction models to single-difference observations, (6) optionally applying ionospheric correction models to single-difference observations, (7) forming one or more linear combinations of carrier phase and pseudorange observations for each satellite - e.g.Optional formation of an ionosphere-free carrier-phase combination with a single difference, a narrow-gauge pseudorange combination with a single difference, etc. Linear combinations have certain important characteristics that are exploited during position calculations. For example, ionosphere-free combinations are essentially free of ionospheric influence. Single-differencing GNSS observations (in a situation where differential processing is possible) helps reduce the impact of satellite-dependent error sources. Satellite clock errors are essentially removed by single-differencing between the base and reconnaissance element receiver data collected at the same time (epoch).When single differencing is not applicable, such as for network processing of a reference station or a precise point fix where there is no single base station, data preparation optionally requires combining reconnaissance element receiver observations with other corrections, such as network correction data created from observations of the GNSS signals acquired at multiple reference stations, or, in the case of a precise point fix, satellite orbit and satellite clock correction data.

[0079] The prepared GNSS signal data 415 is fed to a filter element 420, which estimates values ​​for states of a filter state vector that includes states for receiver position, receiver clock, and carrier phase ambiguities, and optionally includes states for atmospheric influences, such as the ionosphere and troposphere, and states for multipath errors and / or other error-modeled error sources. The result is an array 425 of estimated values ​​for the states of the state vector with associated statistical data. At 430, an estimated position 435 of the receiver is optionally created and reported.

[0080] Fig. 5 schematically forms an architecture 500 for executing the GNSS signal processing flow Fig.4 according to some embodiments of the invention. The GNSS signal data group 405 is optionally prepared in a data preparation element 510 for subsequent filtering. The prepared GNSS signal data 415 is fed to a filter element 420, which estimates the array 445 of estimated values ​​for the states of the state vector with associated statistical data. An optional position calculation element 530 estimates and reports an estimated position 435 of the receiver.

[0081] Fig. 6 shows a variant 600 of the process flow from Fig. 4 similar to that described in US patent US 7 432 853 B2 with reference to Fig. 5 of this patent. In the embodiment of Fig.6, the estimation process 420 is divided into two parts: at 620, the application of a geometry filter that uses a geometry-carrier phase combination to obtain an array 625 of state estimates for the geometry-carrier phase combination with associated statistical information, and at 630, the application of a single bank of geometry-free filters that use geometry-free combinations to obtain an array 635 of state estimates for the geometry-free combinations with associated statistical information. At 640, the arrays 625 and 635 are combined to form the array 425 of state estimates with associated statistical data. The linear nature of the above observation equations (1) and (2) allows a linear combination of the arrays 625 and 635, and the combined result is consistent with the array 425 of Fig.4 is identical. At 430, an estimated position 435 of the receiver is optionally created and reported.

[0082] Fig. 7 shows a variant 700 of the architecture from Fig. 5 similar to that described in US patent US 7 432 853 B2. In the embodiment of Fig.7, the estimation filter element 520 is divided into two parts: at 720, a geometry filter that uses a geometry-carrier phase combination to obtain an array 625 of state estimates for the geometry-carrier phase combination with associated statistical information, and at 730, a single bank of geometry-free filters that use geometry-free combinations to obtain an array 635 of state estimates for the geometry-free combinations with associated statistical information. The combination element 740 combines the arrays 625 and 635 to form the array 425 of state estimates with associated statistical data. The optional position calculation element 430 creates and reports an estimated position 435 of the receiver.

[0083] Fig. 8 schematically depicts a higher level GNSS signal processing flow 800 according to some embodiments of the invention. Fig.8 shows a variant 800 of the process flow from Fig. 4 similar to that described in US patent US 7 432 853 B2 with reference to Fig. 6, Fig. 15, Fig. 16 and Fig. 17 of this patent. In the embodiment of Fig.8, the estimation process 420 is divided into several parts: at 810, applying a geometry filter that uses a geometry-carrier phase combination to obtain an array 830 of estimates for the geometry-carrier phase combination with associated statistical information; at 815, applying a bank of ionospheric filters (one filter per satellite) that use an ionospheric-carrier phase combination to obtain an array 835 of estimates for the ionospheric-carrier phase combination; at 820, optionally applying one or more banks of additional filters 820 (also called "quintessence" or "Q" filters, one filter per bank per satellite) that use ionospheric-free carrier phase combinations to obtain an array 840 of estimates for the ionospheric-free carrier phase combinations;at 825 optionally applying one or more banks of code filters (one filter per bank per satellite) that use ionosphere-free code-carrier combinations to obtain an array 845 of estimates for the ionosphere-free code-carrier combinations;

[0084] At 850, arrays 830, 835, 840, and 845 are combined to form an array 425 of state estimates with associated statistical data. The linear nature of the observation equations (1) and (2) above allows a linear combination of arrays 830, 835, 840, and 845, and the combined result is identical to array 425 of Fig. 4 is identical. At 430, an estimated position 435 of the receiver is optionally created and reported.

[0085] Fig. 9 shows a variant 900 of the architecture from Fig. 5, which is similar to the one described in US patent US 7 432 853 B2 relating to Fig. 8, Fig. 9, Fig. 10, Fig.11A, Fig. 11B, Fig. 12A, Fig. 12B, Fig. 13 and Fig. 14 of this patent. In the embodiment of Fig.8, the filter element 520 is divided into several parts: a geometry filter 910 that uses a geometry-carrier phase combination to obtain an array 830 of estimates for the geometry-carrier phase combination with associated statistical information; a bank 915 of ionospheric filters (one filter per satellite) that use an ionospheric-carrier phase combination to obtain an array 835 of estimates for the ionospheric-carrier phase combination; optionally, one or more banks 920 of additional filters (also referred to as "quintessence" or "Q" filters, one filter per bank per satellite) that use ionospheric-free carrier phase combinations to obtain an array 840 of estimates for the ionospheric-free carrier phase combinations;one or more optional banks 925 of code filters (one filter per bank per satellite) using ionosphere-free code-carrier combinations to obtain an array 845 of estimates for the ionosphere-free code-carrier combinations;

[0086] For example, the maximum number of banks 920 of additional filters is two fewer than the number of observed satellite carrier frequencies. For example, a single bank of additional filters 920 is provided for satellites with three observed carrier frequencies, with up to one filter per three-frequency satellite, and two banks of additional filters 920 are provided for satellites with four observed carrier frequencies, with each bank having up to one filter per four-frequency satellite.

[0087] A certain number of banks 925 of code filters may be provided, up to the number of observed carrier frequencies. For example, one or two banks 925 of code filters may be provided for satellites having two observed carrier frequencies, with each bank having up to one filter per two-frequency satellite. A number of banks of auxiliary code filters may be provided, up to the number of observed carrier frequencies. For example, one or two or three banks of auxiliary code filters may be provided for satellites having three observed carrier frequencies, with each bank having up to one filter per three-frequency satellite. Similarly, any number of one to four code filter banks is provided for a satellite having four carrier frequencies, with each bank having up to one filter per four-frequency satellite.

[0088] Some embodiments according to the invention use a federated geometry filter as described in patent application US 2009 / 0027264, CHEN, X. and VOLLATH U., "GNSS-Signal Processing Methods and Apparatus", dated January 29, 2009.

[0089] Some embodiments according to the invention use ionospheric filters as described in the international patent specification WO 2007 / 032 947 A1.

[0090] The optional position calculation element 430 creates and reports an estimated position 435 of the receiver. The receiver position 435 is calculated as a floating-point solution or as another type of positioning solution, such as fixed-point or a combination of floating and fixed-point, as described in the US patent, or is determined using a weighted average of ambiguities, US 7 432 853 B2, or using techniques described in S. VERHAGEN, "The GNSS-integer ambiguities: estimation and validation", Delft University of Technology, 2004, ISBN 90-804147-4-3, also published in PUBLICATIONS ON GEODESY 58, Delft, 2005, ISBN-13: 978 90 6132 290 0, ISBN-10: 90 6132 290, which are hereby incorporated by reference.

[0091] Additional features of some embodiments of the invention include the following: 1 (Dual Frequency) A method for processing a group of GNSS signal data derived from observations of GNSS signals from multiple transmitters over multiple epochs, the GNSS signals comprising a first signal and a second signal on a first band that can be tracked as a single broadband signal and each of which can be tracked separately, comprising the following steps: a. Obtaining carrier phase observations of the first signal, b. Obtaining carrier phase observations of the second signal, c. Obtaining code observations of the broadband signal, and d. estimating, from a set of observables comprising the carrier phase observations of the first signal, the carrier phase observations of the second signal, and the code observations of the broadband signal, values ​​for a set of parameters comprising: the position of a receiver of the GNSS signals, the clock error of a receiver of the GNSS signals, and an array of ambiguities comprising an ambiguity for each transmitter from which carrier phase observations of the first signal are obtained and an ambiguity for each transmitter from which carrier phase observations of the second signal are obtained. 2 (AltBOC) Method according to item 1, wherein the first signal and the second signal are respective spectral components of a single alternative binary offset carrier modulation. 3 (E5ab) Method according to one of items 1 to 2, wherein the first band is the Galileo E5 band, the only wideband signal is the Galileo E5ab signal, the first signal is the Galileo E5a signal and the second signal is the Galileo Eb5 signal. 4 (Triple frequency) The method of any one of items 1 to 3, wherein the GNSS signals comprise a third signal on a second band, the method further comprising obtaining carrier phase observations of the third signal, the set of observables further comprising the carrier phase observations of the third signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the third signal are obtained. 5 (E1) The method of item 4, wherein the second band is the Galileo band E2-L1-E1 and the third signal is the Galileo E1 signal. 6 (Quad Frequency) The method of any one of items 1 to 5, further comprising obtaining carrier phase observations of the wideband signal, wherein the set of observables further comprises the carrier phase observations of the wideband signal, and wherein the array of ambiguities further comprises an ambiguity for each transmitter from which carrier phase observations of the wideband signal are obtained. 7 (alternative quadruple or quintuple frequency) The method of any one of items 1 to 6, wherein the GNSS signals comprise a fourth signal on a third band, the method further comprising obtaining carrier phase observations of the fourth signal, the set of observables further comprising the carrier phase observations of the fourth signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the fourth signal are obtained. 8 (E6) Method according to item 7, wherein the third band is the Galileo E6 band and the fourth signal is the Galileo E6 signal. 9 (Double Code) Method according to one of items 1 to 8, wherein the method further comprises obtaining code observations of the first signal, and wherein the group of observables further comprises the code observations of the first signal. 10 (alternatively double or triple code) The method of any one of items 1 to 9, wherein the method further comprises obtaining code observations of the second signal, and wherein the set of observables further comprises the code observations of the second signal. 11 (alternative double or alternative triple or quadruple code) The method of any one of items 1 to 10, wherein the method further comprises obtaining code observations of the third signal, and wherein the set of observables further comprises the code observations of the third signal. 12 (alternative double or alternative triple or alternative quadruple or quintuple code) The method of any one of items 1 to 11, wherein the method further comprises obtaining code observations of the fourth signal, and wherein the set of observables further comprises the code observations of the fourth signal. 13 (conventional large filter) The method of any one of items 1 to 12, wherein estimating the parameter group comprises applying to the group of observations a filter having a plurality of states corresponding to parameters of the parameter group. 14 (separate geometry filter) Method according to one of the items 1 to 12, wherein the estimation of the parameter group comprises the following steps: i. applying to the set of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. Applying to the set of GNSS signal data a bank of geometry-free filters that use geometry-free combinations to obtain an array of ambiguity estimates for the geometry-free combinations and associated statistical information; and iii. Combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the geometry-free carrier phase combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. 15 (FAMCAR 2-frequency) Method according to one of the items 1 to 12, wherein the estimation of the parameter group comprises the following steps: i. applying to the set of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. Applying to the set of GNSS signal data a bank of ionospheric filters using geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; iii. Applying to the set of GNSS signal data at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information; and iv. Combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to yield a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. 16 (FAMCAR 3+ Frequency) Method according to one of the items 4 to 12, wherein the estimation of the parameter group comprises the following steps: i. applying to the set of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. Applying to the set of GNSS signal data a bank of ionospheric filters using geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; iii. applying to the set of GNSS signal data at least one bank of additional (quintessence or 'Q') filters using a geometry-free and ionosphere-free carrier phase combination to obtain an array of ambiguity estimates for the geometry-free and ionosphere-free carrier phase combination and associated statistical information; iv. Applying to the set of GNSS signal data at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information; and v. Combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information, and the array of ambiguity estimates for the geometry-free and ionospheric-free carrier phase combination and associated statistical information, and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to yield a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. 17 (Floating Point Solution) The method of any one of items 1 to 16, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, and wherein the method further comprises reporting the estimated position of the receiver. 18 (Fixed-point solution) The method of any one of items 1 to 17, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating-point value, the method further comprising the steps of: setting at least a subset of the array of ambiguities as integer values ​​and reporting the estimated position of the receiver. 19 (iFlex Solution) The method of any one of items 1 to 17, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, the method further comprising the steps of: assigning integer values ​​to at least a subset of the array of ambiguities to define a plurality of candidate groups; determining a quality measure for each of the candidate groups; and obtaining a weighted average of at least a subset of the candidate groups, each candidate group of the weighted average being weighted based on its quality measure. 20 (Corrections) Method according to one of items 1 to 19, further comprising applying corrections to the observations before estimating the group of parameters from the group of observables. 21 (Differential Corrections) The method of item 20, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, and the corrections comprise observations of GNSS signals acquired at a reference receiver, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with the observations acquired at the reference receiver to achieve differential observations, wherein estimating values ​​for the set of parameters comprises estimating the values ​​from the differential observations, and wherein estimating values ​​for the set of parameters comprises estimating a position of the reconnaissance element receiver. 22 (Network Corrections) The method of item 20, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, and the corrections are derived from observations of GNSS signals acquired at a plurality of reference receivers, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with the virtual reference station data to achieve network-corrected observations, wherein estimating values ​​for the parameter group comprises estimating values ​​from the network-corrected observations, and wherein estimating values ​​for the parameter group comprises estimating a position of the reconnaissance element receiver. 23 (PPP Corrections) The method of item 20, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, wherein the corrections comprise satellite orbit data and satellite clock data, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with the satellite orbit data and the satellite clock data to obtain corrected observations, wherein estimating values ​​for the parameter group comprises estimating the values ​​from the corrected observations, and wherein estimating values ​​for the parameter group comprises estimating a position of the reconnaissance element receiver. 24 (Real-time) Method according to one of items 1 to 23, wherein the estimation of values ​​for the parameter group is carried out substantially in real time. 25 (Post-processing) A method according to any one of items 1 to 23, wherein the estimation of values ​​for the parameter group is carried out in a post-processing operation which is substantially not in real time. 26 (Dual Frequency) Apparatus for processing a group of GNSS signal data derived from observations of GNSS signals from multiple transmitters over multiple epochs, the GNSS signals comprising a first signal and a second signal on a first band that can be tracked as a single broadband signal and each of which can be tracked separately, comprising: a. an element for obtaining carrier phase observations of the first signal, b. an element for obtaining carrier phase observations of the second signal, c. an element for obtaining or maintaining code observations of the broadband signal, and d. a filter element for estimating, from a group of observables comprising the carrier phase observations of the first signal, the carrier phase observations of the second signal and the code observations of the broadband signal, values ​​for a group of parameters comprising: the position of a receiver of the GNSS signals, the clock error of a receiver of the GNSS signals and an array of ambiguities comprising an ambiguity for each transmitter from which carrier phase observations of the first signal are obtained and an ambiguity for each transmitter from which carrier phase observations of the second signal are obtained. 27 (AltBOC) Device according to item 26, wherein the first signal and the second signal are respective spectral components of a single alternative binary offset carrier modulation. 28 (E5ab) Apparatus according to any one of items 26 to 27, wherein the first band is the Galileo E5 band, the only wideband signal is the Galileo E5ab signal, the first signal is the Galileo E5a signal and the second signal is the Galileo Eb5 signal. 29 (triple frequency) Apparatus according to any one of items 26 to 28, wherein the GNSS signals comprise a third signal on a second band, the apparatus further comprising an element for obtaining carrier phase observations of the third signal, the set of observables further comprising the carrier phase observations of the third signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the third signal are obtained. 30 (E1) Apparatus according to item 29, wherein the second band is the Galileo band E2-L1-E1 and the third signal is the Galileo E1 signal. 31 (quadruple frequency) Apparatus according to any one of items 26 to 30, further comprising an element for obtaining carrier phase observations of the wideband signal, wherein the set of observables further comprises the carrier phase observations of the wideband signal, and wherein the array of ambiguities further comprises an ambiguity for each transmitter from which carrier phase observations of the wideband signal are obtained. 32 (alternatively quadruple or quintuple frequency) Apparatus according to any one of items 26 to 31, wherein the GNSS signals comprise a fourth signal on a third band, the apparatus further comprising an element for obtaining carrier phase observations of the fourth signal, the set of observables further comprising the carrier phase observations of the fourth signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the fourth signal are obtained. 33 (E6) Apparatus according to item 32, wherein the third band is the Galileo E6 band and the fourth signal is the Galileo E6 signal. 34 (dual code) Apparatus according to any one of items 26 to 33, wherein the apparatus further comprises an element for obtaining code observations of the first signal, and wherein the set of observables further comprises the code observations of the first signal. 35 (alternatively double or triple code) Apparatus according to any one of items 26 to 34, wherein the apparatus further comprises obtaining code observations of the second signal, and wherein the set of observables further comprises the code observations of the second signal. 36 (alternative double or alternative triple or quadruple code) Apparatus according to any one of items 26 to 35, wherein the apparatus further comprises an element for obtaining code observations of the third signal, and wherein the set of observables further comprises the code observations of the third signal. 37 (alternative double or alternative triple or alternative quadruple or quintuple code) Apparatus according to any one of items 26 to 36, wherein the apparatus further comprises an element for obtaining code observations of the fourth signal, and wherein the set of observables further comprises the code observations of the fourth signal. 38 (conventional large filter) Apparatus according to any one of items 26 to 37, wherein the filter element comprises a filter having a plurality of states corresponding to parameters of the parameter group. 39 (separate geometry filter) Device according to one of items 26 to 37, wherein the filter element comprises: i. a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. a bank of geometry-free filters that use geometry-free combinations to obtain an array of ambiguity estimates for the geometry-free combinations and associated statistical information; and iii. a combining element for combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the geometry-free carrier phase combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. 40 (FAMCAR 2-frequency) Device according to one of the items 26 to 37, wherein the filter element comprises: i. a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. a bank of ionospheric filters using geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; iii. at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information; and iv. a combining element for combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to yield a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. 41 (FAMCAR 3+ Frequency) Device according to one of items 29 to 37, wherein the filter element comprises: i. a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. a bank of ionospheric filters using geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; iii. at least one bank of additional (quintessence or 'Q') filters using a geometry-free and ionosphere-free carrier-phase combination to obtain an array of ambiguity estimates for the geometry-free and ionosphere-free carrier-phase combination and associated statistical information; iv. at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information; and v. a combining element for combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information, the array of ambiguity estimates for the geometry-free and ionospheric-free carrier phase combination and associated statistical information, and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to achieve a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. 42 (Floating point solution) Apparatus according to any one of items 26 to 41, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, and wherein the apparatus further comprises an element for reporting the estimated position of the receiver. 43 (Fixed Point Solution) Apparatus according to any one of items 26 to 41, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, the apparatus further comprising: a setting element for setting at least a subset of the arrays of ambiguities as integer values, and for reporting the estimated position of the receiver. 44 (Weighted Solution) Apparatus according to any one of items 26 to 41, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, the apparatus further comprising: an assignment element for assigning integer values ​​to at least a subset of the arrays of ambiguities to define a plurality of candidate groups; a quality element for determining a quality measurement for each of the candidate groups; and an averaging element for obtaining a weighted average of at least a subset of the candidate groups, each candidate group of the weighted average being weighted based on its quality measurement. 45 (Corrections) Apparatus according to any one of items 26 to 44, further comprising a correction element for applying corrections to the observations and for supplying corrected observations to the filter element. 46 (Differential Corrections) Apparatus according to item 45, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, and the corrections comprise observations of GNSS signals acquired at a reference receiver, wherein the correction element is operable to combine observations acquired at the reconnaissance element receiver with observations acquired at the reference receiver to achieve differential observations, wherein the filter element is operable to estimate values ​​for the group of parameters from the differential observations, and wherein the filter element is operable to estimate a position of the reconnaissance element receiver.47 (Network Corrections) Apparatus according to item 45, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, and the corrections are derived from observations of GNSS signals acquired at a plurality of reference receivers, the correction element being operable to combine the observations acquired at the reconnaissance element receiver with the virtual reference station data to achieve corrected observations, the filtering element being operable to estimate values ​​for the parameter group from the corrected observations, and the filtering element being operable to estimate a position of the reconnaissance element receiver. 48 (PPP Corrections) Apparatus according to item 45, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, wherein the corrections comprise satellite orbit data and satellite clock data, wherein the correction element is operable to combine the observations acquired at the reconnaissance element receiver with the satellite orbit data and the satellite clock data to achieve corrected observations, wherein the filter element is operable to estimate values ​​for the parameter group from the corrected observations, and wherein the filter element is operable to estimate a position of the reconnaissance element receiver. 49 (Real-time) Apparatus according to any one of items 26 to 48, wherein the filter element is operable to estimate values ​​for the parameter group substantially in real time. 50 (Post-processing) Apparatus according to any one of items 26 to 48, wherein the filter element is operable to estimate values ​​for the group of parameters in a post-processing operation which is substantially non-real time. 51 Reconnaissance element receiver comprising a device according to any of items 26 to 50. 52 Network station comprising a device as defined in any of items 26 to 50. 53 Computer program comprising instructions configured to carry out a method according to any one of items 1 to 25 when executed on a computer processing unit. 54 Computer-readable medium containing a computer program as defined in item 53.

[0092] Any number of the above-described aspects of the invention may be combined to form further aspects and embodiments with the aim of providing additional advantages, particularly with regard to convergence speed, recovery from jumps and / or system usability.

[0093] All of the devices and their embodiments described above can be integrated into a reconnaissance element, a reference receiver, or a network station, and / or the described processing methods can be performed in a processor separate and even remote from the receivers used to collect the observations (e.g., observation data collected by one or more receivers can be retrieved from memory for post-processing, or observations from multiple networked reference stations can be transmitted to a network processor for near-real-time processing to generate a correction data stream and / or messages from virtual reference stations that can be transmitted to one or more reconnaissance elements). Therefore, the invention also relates to a reconnaissance element, a reference receiver, or a network station comprising any of the above devices.

[0094] In one embodiment, the receiver of the device of any of the embodiments described above is separate from the filter and the processing element. In particular, it is possible to perform post-processing and network processing of the observations. This means that the components of the device for processing observations do not themselves require a receiver. The receiver can be separate from, and even belong to / operate by, a different entity than the entity performing the processing. For post-processing, the observations can be retrieved from a previously collected and stored data set and processed using previously collected and stored reference station data; the processing is performed, for example, on an office computer long after the data collection and thus not in real time.For network processing, multiple reference station receivers collect observations of signals from multiple satellites, and this data is fed to a network processor, which may, for example, generate a correction data stream, or generate a "virtual reference station" correction that is fed to a reconnaissance element so that the reconnaissance element can perform differential processing. The data provided to the reconnaissance element may be ambiguities determined in the network processor that the reconnaissance element can use to accelerate its position solution, or may be in the form of corrections that the reconnaissance element applies to improve its position solution. The network is typically operated as a service to reconnaissance element operators, while the network operator is typically a different entity than the operator of the reconnaissance elements.This applies to all of the devices and claims described above.

[0095] All of the methods described above, as well as their embodiments, can be implemented using a computer program. The computer program can be loaded onto a device, an exploration element, a reference receiver, or a network station as described above. Therefore, the invention also relates to a computer program that, when executed on a device, an exploration element, a reference receiver, or a network station as described above, executes one of the methods described above and their embodiments.

[0096] The invention also relates to a computer-readable medium or a computer program product comprising the above-mentioned computer program. The computer-readable medium or the computer program product can be, for example, a magnetic tape, an optical storage disk, a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD, a CD, a flash memory unit, or the like, on which the computer program is permanently or temporarily stored. The invention also relates to a computer-readable medium (or a computer program product) comprising computer-executable instructions for carrying out one of the methods according to the invention.

[0097] The invention also relates to a firmware update suitable for installation on receivers already in use, i.e., a computer program delivered to the field as a computer program product. This applies to all methods and devices described above.

[0098] GNSS receivers may include an antenna configured to receive the signals at the frequencies emitted by the satellites, processor units, one or more accurate clocks (such as crystal oscillators), one or more computer processing units (CPUs), one or more memory units (RAM, ROM, flash memory, or the like), and a display for showing position information to a user.

[0099] When the terms "receiver," "filter," and "processing element" are used herein as units of a device, there is no restriction on the distribution of the components of a unit. This means that the components of a unit may be distributed across various software or hardware components or devices to implement the intended function. Furthermore, the units may be combined to perform their functions through a combined, single unit. For example, the receiver, filter, and processing element may be combined to form a single unit to perform the combined functionalities of the units.

[0100] The above-mentioned units may be implemented using hardware, software, a combination of hardware and software, pre-programmed ASICs (application-specific integrated circuits), etc. A unit may include a computer processing unit (CPU), a memory unit, input / output (I / O) units, network connection units, etc.

[0101] Although the present invention has been described based on detailed examples, the detailed examples are intended only to provide a better understanding to those skilled in the art and are not intended to limit the scope of the invention. Rather, the scope of the invention is defined by the appended claims.

Claims

[1] A method for processing a group of GNSS signal data derived from observations of GNSS signals from multiple transmitters over multiple epochs, the GNSS signals comprising a first signal and a second signal on a first band that can be tracked as a single broadband signal and each of which can be tracked separately, comprising the following steps: a. Obtaining carrier phase observations of the first signal, b. Obtaining carrier phase observations of the second signal, c. Obtaining code observations of the broadband signal, and d. Estimating, from a set of observables comprising the carrier phase observations of the first signal, the carrier phase observations of the second signal, and the code observations of the broadband signal, values ​​for a set of parameters comprising: the position of a receiver of the GNSS signals, the clock error of a receiver of the GNSS signals, and an array of ambiguities comprising an ambiguity for each transmitter from which carrier phase observations of the first signal are obtained and an ambiguity for each transmitter from which carrier phase observations of the second signal are obtained. [2] The method of claim 1, wherein the first signal and the second signal are respective spectral components of a single alternative binary offset carrier modulation. [3] The method of claim 1, wherein the first band is the Galileo E5 band, the single wideband signal is the Galileo E5ab signal, the first signal is the Galileo E5a signal, and the second signal is the Galileo Eb5 signal. [4] The method of claim 1, wherein the GNSS signals comprise a third signal on a second band, the method further comprising obtaining carrier phase observations of the third signal, the set of observables further comprising the carrier phase observations of the third signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the third signal are obtained. [5] The method of claim 4, wherein the second band is the Galileo band E2-L1-E1 and the third signal is the Galileo E1 signal. [6] The method of claim 1, further comprising obtaining carrier phase observations of the wideband signal, wherein the set of observables further comprises the carrier phase observations of the wideband signal, and wherein the array of ambiguities further comprises an ambiguity for each transmitter from which carrier phase observations of the wideband signal are obtained. [7] The method of claim 1, wherein the GNSS signals comprise a fourth signal on a third band, the method further comprising obtaining carrier phase observations of the fourth signal, wherein the set of observables further comprises the carrier phase observations of the fourth signal, and wherein the array of ambiguities further comprises an ambiguity for each transmitter from which carrier phase observations of the fourth signal are obtained. [8] The method of claim 7, wherein the third band is the Galileo E6 band and the fourth signal is the Galileo E6 signal. [9] The method of claim 1, wherein the method further comprises obtaining code observations of the first signal, and wherein the set of observables further comprises the code observations of the first signal. [10] The method of claim 1, wherein the method further comprises obtaining code observations of the second signal, and wherein the set of observables further comprises the code observations of the second signal. [11] The method of claim 4, wherein the method further comprises obtaining code observations of the third signal, and wherein the set of observables further comprises the code observations of the third signal. [12] The method of claim 7, wherein the method further comprises obtaining code observations of the fourth signal, and wherein the set of observables further comprises the code observations of the fourth signal. [13] The method of claim 1, wherein estimating the set of parameters comprises applying to the set of observations a filter having a plurality of states corresponding to parameters of the set of parameters. [14] The method of claim 1, wherein estimating the parameter group comprises the following steps: i. Applying to the set of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. Applying to the set of GNSS signal data a bank of geometry-free filters that use geometry-free combinations to obtain an array of ambiguity estimates for the geometry-free combinations and associated statistical information; and iii. Combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the geometry-free carrier phase combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. [15] The method of claim 1, wherein estimating the parameter group comprises the following steps: i. Applying to the set of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. Applying to the set of GNSS signal data a bank of ionospheric filters using geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; iii. Applying to the set of GNSS signal data at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information; and iv. Combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. [16] The method of claim 4, wherein estimating the parameter group comprises the following steps: i. Applying to the set of observations a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. Applying to the set of GNSS signal data a bank of ionospheric filters using geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; iii. applying to the set of GNSS signal data at least one bank of additional (quintessence or 'Q') filters using a geometry-free and ionosphere-free carrier phase combination to obtain an array of ambiguity estimates for the geometry-free and ionosphere-free carrier phase combination and associated statistical information; iv. Applying to the set of GNSS signal data at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information; and v. Combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information, the array of ambiguity estimates for the geometry-free and ionospheric-free carrier phase combination and associated statistical information, and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. [17] The method of claim 1, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, and wherein the method further comprises reporting the estimated position of the receiver. [18] The method of claim 1, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, the method further comprising the steps of: Specifying at least a subset of the array of ambiguities as integer values, and reporting the estimated position of the receiver. [19] The method of claim 1, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, the method further comprising the steps of: Assigning integer values ​​to at least a subset of the array of ambiguities to define a plurality of candidate groups; determining a quality measure for each of the candidate groups; and obtaining a weighted average of at least a subset of the candidate groups, wherein each candidate group of the weighted average is weighted based on its quality measure. [20] The method of claim 1, further comprising applying corrections to the observations prior to estimating the set of parameters from the set of observables. [21] The method of claim 20, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver and the corrections comprise observations of GNSS signals acquired at a reference receiver, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with the observations acquired at the reference receiver to obtain differential observations, wherein estimating values ​​for the set of parameters comprises estimating the values ​​from the differential observations, and wherein estimating values ​​for the set of parameters comprises estimating a position of the reconnaissance element receiver. [22] The method of claim 20, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver and the corrections are derived from observations of GNSS signals acquired at a plurality of reference receivers, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with virtual reference station data to obtain network-corrected observations, wherein estimating values ​​for the set of parameters comprises estimating the values ​​from the network-corrected observations, and wherein estimating values ​​for the set of parameters comprises estimating a position of the reconnaissance element receiver. [23] The method of claim 20, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, wherein the corrections comprise satellite orbit data and satellite clock data, wherein applying corrections to the observations comprises combining the observations acquired at the reconnaissance element receiver with the satellite orbit data and the satellite clock data to obtain corrected observations, wherein estimating values ​​for the set of parameters comprises estimating the values ​​from the corrected observations, and wherein estimating values ​​for the set of parameters comprises estimating a position of the reconnaissance element receiver. [24] The method of claim 1, wherein estimating values ​​for the parameter group is performed in real time. [25] The method of claim 1, wherein the estimation of values ​​for the parameter group is performed in a post-processing operation that is not in real time. [26] An apparatus for processing a group of GNSS signal data derived from observations of GNSS signals from multiple transmitters over multiple epochs, the GNSS signals comprising a first signal and a second signal on a first band that can be tracked as a single broadband signal and each of which can be tracked separately, comprising: a. an element for obtaining carrier phase observations of the first signal, b. an element for obtaining carrier phase observations of the second signal, c. an element for obtaining code observations of the broadband signal, and d. a filter element for estimating, from a group of observables comprising the carrier phase observations of the first signal, the carrier phase observations of the second signal, and the code observations of the broadband signal, values ​​for a group of parameters comprising: the position of a receiver of the GNSS signals, the clock error of a receiver of the GNSS signals, and an array of ambiguities comprising an ambiguity for each transmitter from which carrier phase observations of the first signal are obtained and an ambiguity for each transmitter from which carrier phase observations of the second signal are obtained. [27] Apparatus according to claim 26, wherein the first signal and the second signal are respective spectral components of a single alternative binary offset carrier modulation. [28] Apparatus according to claim 26, wherein the first band is the Galileo E5 band, the single wideband signal is the Galileo E5ab signal, the first signal is the Galileo E5a signal and the second signal is the Galileo Eb5 signal. [29] The apparatus of claim 26, wherein the GNSS signals comprise a third signal on a second band, the apparatus further comprising an element for obtaining carrier phase observations of the third signal, the set of observables further comprising the carrier phase observations of the third signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the third signal are obtained. [30] Apparatus according to claim 29, wherein the second band is the Galileo band E2-L1-E1 and the third signal is the Galileo E1 signal. [31] The apparatus of claim 26, further comprising an element for obtaining carrier phase observations of the wideband signal, wherein the set of observables further comprises the carrier phase observations of the wideband signal, and wherein the array of ambiguities further comprises an ambiguity for each transmitter from which carrier phase observations of the wideband signal are obtained. [32] The apparatus of claim 26, wherein the GNSS signals comprise a fourth signal on a third band, the apparatus further comprising an element for obtaining carrier phase observations of the fourth signal, the set of observables further comprising the carrier phase observations of the fourth signal, and the array of ambiguities further comprising an ambiguity for each transmitter from which carrier phase observations of the fourth signal are obtained. [33] Apparatus according to claim 32, wherein the third band is the Galileo E6 band and the fourth signal is the Galileo E6 signal. [34] The apparatus of claim 26, wherein the apparatus further comprises an element for obtaining code observations of the first signal, and wherein the set of observables further comprises the code observations of the first signal. [35] The apparatus of claim 26, wherein the apparatus further comprises obtaining code observations of the second signal, and wherein the set of observables further comprises the code observations of the second signal. [36] The apparatus of claim 29, wherein the apparatus further comprises an element for obtaining code observations of the third signal, and wherein the set of observables further comprises the code observations of the third signal. [37] The apparatus of claim 32, wherein the apparatus further comprises an element for obtaining code observations of the fourth signal, and wherein the set of observables further comprises the code observations of the fourth signal. [38] The apparatus of claim 26, wherein the filter element comprises a filter having a plurality of states corresponding to parameters of the parameter group. [39] Apparatus according to claim 26, wherein the filter element comprises: i. a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. a bank of geometry-free filters that use geometry-free combinations to obtain an array of ambiguity estimates for the geometry-free combinations and associated statistical information; and iii. a combining element for combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the geometry-free carrier phase combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. [40] Apparatus according to claim 26, wherein the filter element comprises: i. a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; ii. a bank of ionospheric filters using geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; iii. at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information; and iv. a combining element for combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. [41] Apparatus according to claim 29, wherein the filter element comprises: v. a geometry filter that uses a geometry-carrier phase combination to obtain an array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information; vi. a bank of ionospheric filters using geometry-free ionospheric-carrier phase combination to obtain an array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information; vii. at least one bank of additional (quintessence or ‘Q’) filters using a geometry-free and ionosphere-free carrier phase combination to obtain an array of ambiguity estimates for the geometry-free and ionosphere-free carrier phase combination and associated statistical information; viii. at least one code filter that uses a plurality of geometry-free code-carrier combinations to obtain an array of ambiguity estimates for the code-carrier combinations and associated statistical information; and ix. a combining element for combining the array of ambiguity estimates for the geometry-carrier phase combination and associated statistical information with the array of ambiguity estimates for the ionospheric-carrier phase combination and associated statistical information, the array of ambiguity estimates for the geometry-free and ionospheric-free carrier phase combination and associated statistical information, and the array of ambiguity estimates for the code-carrier combinations and associated statistical information to obtain a combined array of ambiguity estimates for all carrier phase observations and associated statistical information. [42] The apparatus of claim 26, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, and wherein the apparatus further comprises an element to report the estimated position of the receiver. [43] The apparatus of claim 26, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, the apparatus further comprising: a setting element for setting at least a subset of the array of ambiguities as integer values ​​and for reporting the estimated position of the receiver. [44] The apparatus of claim 26, wherein the ambiguity for each transmitter from which carrier phase observations of the second signal are obtained is a floating point value, the apparatus further comprising: an assignment element for assigning integer values ​​to at least a subset of the array of ambiguities to define a plurality of candidate groups; a quality element for determining a quality measure for each of the candidate groups; and an averaging element for obtaining a weighted average of at least a subset of the candidate groups, each candidate group of the weighted average being weighted based on its quality measure. [45] The apparatus of claim 26, further comprising a correction element for applying corrections to the observations and for supplying corrected observations to the filter element. [46] Apparatus according to claim 45, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver and the corrections comprise observations of GNSS signals acquired at a reference receiver, the correction element being operable to combine observations acquired at the reconnaissance element receiver with observations acquired at the reference receiver to obtain differential observations, the filtering element being operable to estimate values ​​for the group of parameters from the differential observations, and the filtering element being operable to estimate a position of the reconnaissance element receiver. [47] Apparatus according to claim 45, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver and the corrections are derived from observations of GNSS signals acquired at a plurality of reference receivers, the correction element being operable to combine the observations acquired at the reconnaissance element receiver with virtual reference station data to obtain corrected observations, the filtering element being operable to estimate values ​​for the parameter set from the corrected observations, and the filtering element being operable to estimate a position of the reconnaissance element receiver. [48] ​​Apparatus according to claim 45, wherein the observations comprise observations of GNSS signals acquired at a reconnaissance element receiver, the corrections comprising satellite orbit data and satellite clock data, the correction element being operable to combine the observations acquired at the reconnaissance element receiver with the satellite orbit data and the satellite clock data to obtain corrected observations, the filtering element being operable to estimate values ​​for the parameter group from the corrected observations, and the filtering element being operable to estimate a position of the reconnaissance element receiver. [49] Apparatus according to claim 26, wherein the filter element is operable to estimate values ​​for the group of parameters in real time. [50] The apparatus of claim 26, wherein the filter element is operable to estimate values ​​for the group of parameters in a non-real-time post-processing operation. [51] A reconnaissance element receiver comprising a device according to claim 26. [52] A network station comprising a device according to claim 26. [53] A computer program comprising instructions configured to perform a method according to claim 1 when executed on a computer processing unit. [54] A computer-readable medium comprising a computer program according to claim 53.

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