Patent Publication Number: US-11640003-B2

Title: Method for detecting spoofing in a global navigation satellite system receiver, corresponding receiver apparatus and computer program product

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to Italian Patent Application No. 102020000011794, filed on May 20, 2020, which application is hereby incorporated herein by reference. 
     TECHNICAL FIELD 
     Embodiments of the present disclosure relate to detection of a spoofed signal in a GNSS (Global Navigation Satellite System) receiver, and related receiver apparatus and computer program product. The present disclosure in particular describes techniques for detecting a tracking channel affected by a spoofing signal in a GNSS Multi Frequency-Multi Constellation Receiver. 
     BACKGROUND 
     Integrity is a key feature in the transport field, and the increasing availability of low cost “Meaconing”/“Spoofing” systems is a critical issue. 
     A so called “spoofer” can intentionally lead a receiver to estimate a fake position and cause incorrect decisions. 
     Autonomous and assisted driving applications are raising the requirements for on-board GNSS receivers and to have a robust anti-spoofing system operating with such a receiver is a necessity. 
     To detect a spoofing signal and consequently a spoofed signal, i.e., a signal tracked into the tracking channel which is locked on the spoofing signal, into the receiver it is known to perform a method based on Parallel Least Mean Square calculation, which includes executing position identification using more constellations in an independent way and checking the consistency among them. It relies on the assumption that the Spoofing attack is not affecting all the tracked constellations/bandwidths. 
     This solution acts only after the spoofer has taken the tracking channels and needs multifrequency/parallel positioning to survive. 
     Also, other methods use Navigation Message Authentication, which is a Galileo Public Regulated Service (PRS), i.e., an encrypted navigation service for governmental authorized users. Signal Ephemerides are “encrypted” and a key management is required between satellite and PRS receiver. 
     This solution needs PRS Galileo tracking and usage, and is not suitable for a GPS only solution. 
     Also, a further method envisages detecting GPS spoofing with a multiple antenna array, as per https://web.stanford.edu/group/sepnt/gpslab/website_files/anti-spoofing/insideGNSS_rasd-montgomery.pdf. 
     Such a solution relies on the use of additional hardware. 
     SUMMARY 
     In view of the above, it is an objective of the present disclosure to provide solutions which overcome one or more of the above drawbacks. 
     According to one or more embodiments, one or more of the above objectives is achieved by means of a method having the features specifically set forth in the claims that follow. Embodiments moreover concern a related receiver apparatus and computer program product. 
     The claims are an integral part of the technical teaching of the disclosure provided herein. 
     As mentioned before, the present disclosure relates to a method for detecting spoofing in a GNSS receiver, comprising receiving at least a satellite signal, acquiring the satellite signal as received signal, performing a tracking of the received signal including receiving the received signal in at least one tracking channel comprising a bank of correlators receiving in-phase and quadrature versions of the received signal, generating a Pseudo Random Noise sequence at a code frequency set by a code Numerical Controlled Oscillator comprised in the tracking channel determining a code rate, performing a GNSS Pseudo Random Noise delayed sequence generation, including generating, on the basis of a Pseudo Random Noise sequence received from the GNSS Pseudo Random Noise sequence generator, a set of replicas of the Pseudo Random Noise sequence comprising a punctual replica and a plurality of replicas which are early in time or delayed in time with respect to the punctual replica of the Pseudo Random Noise sequence over a given time spacing, correlating the received signal with each replica in the set of replicas of the Pseudo Random Noise sequence to obtain amplitude correlation values, wherein the method includes monitoring at least a tracking channel to detect a spoofed signal by generating a further plurality of replicas of the Pseudo Random Noise sequence of the at least a tracking channel having a respective time spacing greater than the given time spacing, correlating the received signal at least a tracking channel with each replica in the further plurality of replicas of the Pseudo Random Noise sequence to obtain further amplitude correlation values, calculating a shape anomaly factor as a function of the further correlation amplitude values determined by the further plurality of replicas, verifying if the shape anomaly factor is greater than a given shape anomaly threshold, and, in the affirmative, signaling detection of a spoofed signal on the monitored tracking channel. 
     In variant embodiments, the monitoring the at least a tracking channel to detect a spoofed signal includes providing a set of tracking channels comprising a first subset of tracking channels operating with a set of replicas spaced of the given time spacing and a second subset of auxiliary channels which replicas are spaced of the second spacing greater than the given time spacing, the monitoring operation comprising allocating a corresponding monitoring channel comprising a one or more auxiliary tracking channels in the second subset of auxiliary channels, having respective replicas which are spaced of the second spacing greater than the given time spacing, the auxiliary tracking channels receiving the same received signal received by the monitored tracking channel and operating with the same Pseudo Random Noise sequence. 
     In variant embodiments, the monitoring the at least a tracking channel to detect a spoofed signal includes providing a set of tracking channels comprising a first subset of tracking channels operating with a set of replicas spaced of a first delay value and a second subset of auxiliary channels which replicas are spaced of a second delay value greater than the first delay value, the monitoring operation comprising allocating a corresponding monitoring channel comprising a plurality of auxiliary tracking channels in the second subset of auxiliary channels, having respective replicas which are delay shifted one with respect to the other of a third delay. 
     In variant embodiments, the monitoring includes measuring a parameter representative of the input noise on one or more of the tracking channels verifying if the parameter representative of the input noise is greater than given noise threshold in at least one of the tracking channels, and, if a determined tracking channel is above the noise threshold, performing the operation of allocating with respect to the determined tracking channel. 
     In variant embodiments, the parameter representative of the input noise is a weighted sum of discriminator parameters, in particular EML and DD discriminators. 
     In variant embodiments, calculating a shape anomaly factor as a function of the correlation amplitude values of the auxiliary tracking channels includes computing a sum of the differences between the points having nominally the same amplitude correlation values in each auxiliary channel, in particular with respect to the nominal tracked peak point. 
     In variant embodiments, signaling detection of a spoofed signal on the monitored tracking channel includes signaling a spoofing alert. 
     In variant embodiments, signaling detection of a spoofed signal on the monitored tracking channel includes gating the output of the monitored tracking channel. 
     In variant embodiments, signaling detection of a spoofed signal on the monitored tracking channel includes detecting the separation between the spoofed signal and the satellite signal and stopping the tracking channel above a given value of separation, then reacquiring the satellite signal. 
     In variant embodiments, after signaling detection of a spoofed signal the operation of detecting the separation between the spoofed signal and the satellite signal and stopping the tracking channel above a given value of separation, then reacquiring the satellite signal includes performing a runtime consistency check between the satellite predicted position, which is obtained by Ephemerides Extrapolation, and the Range Peak point measurement outputted by the monitored tracking channel, verifying if a spatial separation between the spoofed signal and the original satellite signal is greater than a given separation distance, and, in the affirmative, discarding the current tracked Peak point monitored tracking channel which is determined by the spoofed signal and reacquiring the satellite signal using the predicted position. 
     In variant embodiments, the verifying if the parameter representative of the input noise is above a given noise threshold in at least one of the tracking channels includes verifying if the measured parameter representative of the input noise is greater than corresponding parameters representative of the input noise measured on other tracking channels in the first subset of tracking channels. 
     The present disclosure relates also to a receiver apparatus configured to perform the method of any of the previous embodiments, comprising an arrangement for detecting a spoofed signal comprising a GNSS Pseudo Random Noise sequence generator for generating a further plurality of replicas of the Pseudo Random Noise sequence of the at least a tracking channel having a respective time spacing greater than the given time spacing, the arrangement being further configured to correlate the received signal at least a tracking channel with each replica in the further plurality of replicas of the Pseudo Random Noise sequence to obtain further amplitude correlation values calculate a shape anomaly factor as a function of the further correlation amplitude values determined by the further plurality of replicas, verify if the shape anomaly factor is greater than a given shape anomaly threshold, and, in the affirmative, signal detection of a spoofed signal on the monitored tracking channel. 
     In variant embodiments, the receiver comprises a set of tracking channels comprising a first subset of tracking channels operating with a set of replicas spaced of the given time spacing and a second subset of auxiliary channels which replicas are spaced of the second spacing greater than the given time spacing. 
     In variant embodiments, the receiver comprises a set of tracking channels comprising a first subset of tracking channels operating with a set of replicas spaced of a first delay value and a second sunset of auxiliary channels spaced of a second delay value greater than the first delay value. 
     In variant embodiments, the at least tracking channel includes the arrangement for detecting a spoofed signal, the GNSS Pseudo Random Noise sequence generator generating both the set of replicas of the Pseudo Random Noise sequence with a given spacing and the further plurality of replicas having a respective time spacing greater than the given time spacing. 
     The present disclosure relates also to a computer program product directly loadable into the internal memory of a digital computer, comprising software code portions for performing the steps of the method of any of the previous embodiments. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Embodiments of the present disclosure will now be described with reference to the annexed drawings, which are provided purely by way of non-limiting example and in which: 
         FIG.  1    is a schematic diagram showing a GNSS (Global Navigation Satellite System) system; 
         FIG.  2    is a schematic diagram of a tracking channel operating in a GNSS receiver apparatus; 
         FIGS.  3 ,  4 A and  4 B  are time diagrams of signals formed in the GNSS receiver apparatus of  FIG.  2   ; 
         FIGS.  5 A,  5 B and  5 C , collectively  FIG.  5   , are a schematic time diagram of a monitoring channel and corresponding auxiliary tracking channels; 
         FIG.  6    is a schematic diagram of a tracking channel according to the solution here described; 
         FIGS.  7 A and  7 B , collectively  FIG.  7   , are schematic time diagrams of an example of monitoring channel and corresponding auxiliary tracking channels; 
         FIGS.  8 A,  8 B and  8 C , collectively  FIG.  8   , are schematic time diagrams representing auxiliary tracking channels in a spoofing scenario of operation; 
         FIGS.  9 A and  9 B , collectively  FIG.  9   , are schematic time diagrams of an anomaly shaping parameter in a normal scenario of operation and in spoofing scenario of operation; 
         FIG.  10    is a flow diagram of an embodiment of the method according to the solution here described; and 
         FIG.  11    is a time diagram of signals used by the method of  FIG.  10   . 
     
    
    
     DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS 
     In the following description, numerous specific details are given to provide a thorough understanding of embodiments. The embodiments can be practiced without one or several specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the embodiments. 
     Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. 
     The headings provided herein are for convenience only and do not interpret the scope or meaning of the embodiments. 
     A navigation receiver operates by down converting to quasi baseband the input signal received from the satellites, which is transmitted at L band (1-2 GHz), using a local oscillator to step down the input frequency and allow a baseband digital management of the Satellite information. 
     With reference to  FIG.  1   , which diagrammatically shows a GNSS Global Navigation Satellite System) system  1000  (such as, for example, Global Positioning System (GPS), Global&#39;naya Navigatsionnaya Sputnikovaya Sistema (GLONASS), Galileo System, or other types of satellite-based positioning systems, such global satellite positioning system  1000  comprises a constellation of a number NS of satellites S 1 -S NS  and at least a receiving apparatus  100 . The satellite signals used in the GNSS (Global Navigation Satellite System) are of the CDMA-type (Code Division Multiple Access). The satellite signals reception at the receiving apparatus  100  is implemented through the following, sequentially performed, standard steps: analog filtering, frequency conversion and digitization, acquisition, tracking, decoding and positioning. 
     The receiving apparatus  100  comprises an antenna  1 , an analog receiving module AFE (Analog Front End), provided with a radiofrequency (RF) stage  2 , and an analog-digital converter  3  (ADC), which can be implemented by hardware modules. 
     Further, the receiving apparatus  100  comprises a digital processing module DFE (Digital Front End), including an acquisition module  4  (ACQ), and a tracking module  5  (TRK). 
     Moreover, the receiving apparatus  100  is provided with a sub-frame recovery module (SBF-REC), an ephemerides processing and pseudo-range calculation module  7  (EPH-PSR), a satellites orbits prediction module  8  (ORB-PRE), a satellite type detecting module  9  (MOD-DET), a satellite position calculation module  10  (SAT-POS), and a user position calculation module  11  (USR-POS). 
     In a particular embodiment, acquisition module  4 , tracking module  5  can be implemented by hardware, while the remaining modules  6 - 11  can be implemented by software. In addition, it is observed that the acquisition module  4  and tracking module  5  can also be implemented by a hardware and software combination. 
     The receiving apparatus  100  is provided with a central processing unit, memories (mass memory and/or working storage) and respective interfaces (not shown in figures), comprising a microprocessor or microcontroller, for running the software resident in it. 
     The following embodiments are described in a non-limiting way referring to the GPS technology. However the teachings of the present disclosure can also be applied to other satellite positioning systems. 
     When the receiving apparatus  100  operates, the antenna  1  receives a plurality of signals s 0 , . . . , s NS−1  from one or more satellites S 0 -S NS−1  of the constellation of satellites operating in system  1000 . For example, these signals can be modulated on a carrier having a frequency of about 1.5 GHz. Particularly, each received signal transports a pseudo-random code and a message for the data communication. 
     The pseudo-random code, known as CA code, for example at 1 MHz, is used for distinguishing a satellite from another, and enables the receiving apparatus  100  to measure the time instant at which has been transmitted a signal by a corresponding satellite. Pseudo-random code is implemented by a sequence of pulses, called chips. 
     The radio frequency stage  2  operates on the signals received by antenna  1  (of the analog type) and converts them to the base band or to an intermediate frequency. Analog-digital converter  3  converts the intermediate frequency signals to corresponding digital signals. The radio-frequency stage  2  operates the conversion at an intermediate frequency using the frequency of a local signal LS which may be supplied by a Temperature Compensated Crystal Oscillator (TCXO)  2   a.    
     The acquisition block  4  identifies in the digital signals originated by the analog-digital converter  3  the satellites in visibility, testing their presence by trying to match their transmitted PRN (Pseudo Random Noise) code sequence, i.e., the CA code, with a corresponding local replica and when a peak confirmation is found it provides the initial GNSS information, i.e., code/frequency information to an elementary Intermediate Frequency tracking correlation block. Further, the acquisition module  4  detects a plurality of parameters associated to the satellites and used for time tracking the satellite. 
     The data navigation message transports data (for example at a bit rate equal to 50 Hz) and particularly is modulated based on the Binary Phase Shift Keying (BPSK) technique. Further, data navigation message is hierarchically divided in frames and sub-frames and transports several information, among them a plurality of parameters used for determining the orbit and consequently the position of satellites. 
     The tracking module  5  has plural channels, indicated by a channel index i from 0 to NS−1, in particular indicated as TRK 0  . . . TRK NS−1  and each is allocated to a different satellite of the constellation. Specifically, the tracking module  5  is configured to operate as a frequency locked loop. Based on a further embodiment, tracking module  5  is configured to implement a phase locked loop. 
     The tracking module  5  is configured to supply data to the sub-frame recovery module  6 , as a time sequence of samples pairs, indicated with {I, Q}. Each sample {I, Q} is for example the result of a coherent integration, respectively in-step and quadrature, of a bit of 20 ms, performed by a correlator based on the modulation technique Binary Phase Shift Keying (BPSK). Each samples pair {I, Q} represents a transmitted bit. 
     As it is known in the field of the digital communication theory, each sample {I, Q} can be further interpreted as a phasor, by considering the value I and value Q as the real and imaginary parts of a bi-dimensional vector in the complex Cartesian plane. 
     Moreover, for each satellite, in the tracking module  5  the Doppler frequency and the transfer time of the GPS signal transmitted by a satellite S 1 -S NS  are determined. 
     The sub-frame recovery module  6 , by means of suitable algorithms, decodes the different received sub-frames forming the navigation data message. The ephemerides processing and pseudo-range calculation module  7  stores the satellite orbit, as ephemerides data, and calculates the existent distances between the satellites and the receiving apparatus  100 : such distances are called pseudo-range. By these calculated values, and the time for transferring the GPS signal, the satellite position calculation module  10  calculates the positions of the satellites expressed by 3D coordinates, at the moment of transmission. 
     The satellite orbit prediction module  8  can be activated for assisting the ephemerides processing and pseudo-range calculation module  7  and/or satellite position calculation module  10  when the ephemerides data are not available at the receiving apparatus  100 . 
     The satellite type detecting module  9  is configured to determine the type of the tracked satellite and by it the solar radiation pressure model to be used in the orbit prediction by the satellite orbit prediction module  8 , according to modes that will be described in the following as examples. The satellite type detecting module  9  enables to determine the type of satellite in order to select the solar radiation pressure model which better provides for the shape, mass and size of a satellite. 
     In this embodiment, the satellite position calculation module  10  operates on the time for transferring the GPS signal together with the reception time (known due to a clock inside the receiving apparatus  100 ). The satellite position calculation module  10  operates in order to evaluate how much time is required to the signal from each satellite for reaching the receiving apparatus  100 , evaluating in this way the distance from the corresponding satellite (pseudo-range). 
     By a triangulation algorithm, the user position calculation module  11  calculates the position of the receiving apparatus  100  based on the distances of the receiving apparatus  100  preferably from at least four satellites and based on the positions of the same satellites, known at this processing stage. In the following, the position of the receiving apparatus  100  (practically coinciding with the user position) will be called “fix”. 
     As mentioned, the tracking module  5  includes a plurality of channels, i.e., tracking correlation blocks which are usually let working in parallel each tuned on a different satellite PRN code and frequency, among the ones previously identified by the acquisition block  4 , with the goal to confirm or eventually discard the acquisition hypothesis for every of them. For the confirmed satellites, after a startup refinement of the code and frequency initially provided by the acquisition block, the stable locked tracking phase starts. It consists into tightly following both the frequency offset (velocity) and the code phase (distance) of the satellite vehicle being analyzed and to demodulate the position and time information embedded in its bit stream. This information is then provided to a Kalman Filter to triangulate the receiver position. 
     The tracking channel as mentioned includes a correlator which comprises a PRN (pseudorandom noise) delayed sequence generator. The GNSS signals received at the receiver includes a ranging code modulated into the carrier, also called Pseudo-Random Noise (PRN) code, which spreads the spectrum and allows retrieving ranging information. Therefore, it is required that the tracking channel include a PRN delayed sequence generator, which generates PRN sequences which are early, punctual or delayed one with respect to the other to perform correlation with the ranging codes. 
     In  FIG.  2    it is shown schematically a tracking channel TRK i  comprising an embodiment of a GNNS PRN delayed sequence generator  20 . The GNNS PRN delayed sequence generator  20  basically comprises a GNSS PRN sequence generator  23  and a delayed sequence generator  24 . A code Numerical Controlled Oscillator  32 , NCO in the following, is also provided which is programmed to generate the Pseudo Random Noise, PRN in the following, code rate. For example, for GPS the code rate is Fchip=1.023 MHz. Such code NCO  32  receives a frequency word FW, setting the code rate Fchip, and a clock signal CK from the AFE stage  2 . 
     More in detail, baseband in-step I T  and quadrature Q T  components of the GNSS signal received enter a module  21  configured to remove the frequency Doppler. Such module  21  to this regard receives from a carrier NCO (Numerical Control Oscillator)  22  respective in-step and quadrature frequencies nco_i and nco_q, generated by the carrier NCO  22  under the control of a NCO drive frequency NCOF, which corresponds to the receiver generated carrier. Module  21  therefore generates an in-step wiped component I W  and a quadrature wiped component Q W  of the GNSS received signal where the frequency Doppler (a Doppler Effect frequency offset caused by the reciprocal motions of the satellite and the receiving apparatus) is removed, i.e., wiped, which are brought as input to a bank of correlators  25  arranged in parallel, each of which receives at another input a delayed, punctual or early version of the PRN code generated by a delayed sequence generator  24 . Specifically, in the example shown there are five correlators,  25   1 ,  25   2 ,  25   3 ,  25   4 ,  25   5 , which receive at one input the wiped components I W ,Q W  and at the other input respectively a very early signal E 2  (also VE), an early signal E 1  (also E), a punctual signal P or prompt signal, a late signal L 1  (also L), a very late signal L 2  (also VL), which correspond to time-shifted replicas of the PRN code signal, shifted, as shown in the time diagram of  FIG.  4   , of a given interval of time one with respect of the other, starting from very early signal E 2 , which is early by two intervals of time with respect to punctual signal P, and arriving to very late signal L 2 , which is late by two intervals of time with respect to punctual signal P, which in general corresponds to the so-called Prompt code. Although the example shown refers to K=2 early and late sequences, the value K can be different, one, i.e., only three replicas, early, prompt and late, or greater than two. 
     With the reference number  23  is then indicated a GNSS PRN generator, which receives setting GS and generates a GNSS PRN sequence PS, i.e., PRN codes. The setting GS to originate a given PRN sequence PS are supplied by the acquisition side in the analog receiving module AFE along with the starting phase. The PRN sequence PS is brought as input to the GNSS PRN delayed sequence generator  24  which outputs signals E 2 , E 1 , P, L 1 , L 2 . 
     Each correlator includes a multiplier  251 , which receives the two inputs from the module  21  and PRN generator  24 , and supplies the sum at its output to a respective accumulator register  252 , e.g., an integration and dumping block, which accumulates over an accumulation time of the correlator  25 , and supplies accumulated in-step I acc  and quadrature components Q acc , which are supplied to a receiver processor to evaluate the result of the correlation and to find the correlation peaks. These techniques and the techniques employed to process the accumulated in-step I acc  and quadrature components Q acc  are known per se to the person skilled in the art and would not be further discussed in detail. Thanks to the correlation result with the PRN sequence advanced and delayed versions, the receiver is able to maintain a stable satellite tracking and get a high accuracy by using a discriminator algorithm. 
     As mentioned, in  FIG.  3    it is shown the time diagram of the replica signals E 2 , E 1 , P, L 1 , L 2 , which are delayed one with respect to the other of a time delay D, while in  FIG.  4 A  it is shown the correlation power, in absolute value, as a function of the normalized code phase, i.e., the phase of the replica normalized to the chip duration T c , of such outputs signals, i.e., replicas E 2 , E 1 , P, L 1 , L 2 . Although the abscissa is correlation power, thus points on the curve are absolute correlation power values, e.g., the sum of the square of accumulated in-step I acc  and of the square quadrature components Q acc  for each replica, e.g., I E2   2 +Q E2   2  for the very early replica E 2 , in this and in the following correlation diagrams, e.g.,  FIGS.  4 B,  7 A,  7 B , for simplicity of representation are identified by the labels of the replica labels E 2 , E 1 , P, L 1 , L 2  which originate them. The dotted line connecting the absolute correlation power values represents the tracking correlation curve. The idea is to sample the tracking correlation curve in the right position by the 2K+1 correlation point (5 in this example, with K=2 i.e., E 2 , E 1 , P, L 1 , L 2  signals). 
     As shown in  FIG.  4 B , which shows a logic correlation point diagram, i.e., the power value (I 2 +Q 2 ), i.e., the sum of the square of accumulated in-step I acc  and the square of quadrature components Q acc , of the correlation between the sequence E 2 , E 1 , P, L 1 , L 2  and the incoming signal from the block  252  (in practice it is a sampling of the ideal tracking correlation curve at certain normalized code delay T according to the settings), a maximum delay or time spacing SM/2 between signal E 2  or L 2  and signal P is fixed, thus the total, early-late, spacing SM between replicas, i.e., between signal E 2  and L 2 , is also fixed. 
     To compensate peak tracking error, Very Early, Early, Prompt, Late and Very Late power values, i.e., correlation power values determined by replica signals E 2 , E 1 , P, L 1 , L 2 , are then the input for a discriminator function, i.e., a discriminator module  26 . Its output is used to produce the control feedback signal to align the local replica to the incoming satellite signal, e.g., supplying the control feedback signals to the code NCO  32 . More specifically loop filters are used to obtain code feedback signals and carrier feedback signals. The corresponding modules and circuits are known per se to the person skilled in the art and are not shown for simplicity in  FIG.  2   . 
     The input error/output feedback relationship is technically called S-Curve. 
     Different spacings in time (or delay) of the five amplitude values corresponding to replicas E 2 , E 1 , P, L 1 , L 2  are possible (so different S-curves) and a noisiness estimate for the tracking channel TRK i  is achievable starting from the discriminator output, as also discussed in the following. 
     The most common discriminator functions used to compensate the input residual error are, as shown below, the EML (Early Minus Late, two points, E-L used) and the DD (Double Delta, five points VE . . . P . . . VL used) discriminator.
 
 D   EML =(( I   E1   2   +Q   E1   2 )−( I   L1   2   +Q   L1   2 ))/(( I   E1   2   +Q   E1   2 )+( I   L1   2   +Q   L1   2 ))
 
 D   DD   =a *(( I   E   2   +Q   E   2 )−( I   L   2   +Q   L   2 ))− b *(( I   E2   2   +Q   E2   2 )−( I   L2   2   +Q   L2   2 ))/[(( I   E   2   +Q   E   2 )−( I   L   2   +Q   L   2 ))+(( I   E2   2   +Q   E2   2 )−( I   L2   2   +Q   L2   2 ))],
 
where I, Q are the in-step and quadrature components resulting from the correlation with the different replicas E 2 , E 1 , L 1 , L 2 , indicated by the subscript. a and b are weights which value can be set.
 
     An indication of the correct tracking, i.e., a parameter representative of the input noise, is adopted in the solution here described, indicated with DDM5, which represents a weighted average of the EML and DD discriminator outputs to qualify the tracking goodness:
 
 DDM 5=(α D   EML   +βD   DD )/(α+β),
 
α and β being weights which value can be set in 0 . . . 1 with their sum equal to 1 for normalization, where discriminators D EML  and D DD  are standard DDL discriminators outputs acting on two (E-L) and five (VE-E-P-L-VL) points respectively.
 
     In ideal conditions (tracking without any offset) both EML and DD discriminator outputs are zero and the noise parameter DDM5 is zero as well. The noise parameter DDM5 increases instead with input noise on the received signal s i . 
     According to the solution here described to detect the spoofing, the solution provides a GNSS apparatus analogous to the GNSS apparatus  100  of  FIGS.  1  and  2   , but equipped with a tracking block  5 ′ in which, as shown in  FIG.  6   , there is a set of tracking channels logically divided into: a first number NS of standard tracking channels TRK i , corresponding to the number NS of satellites in the constellation to track, used for standard positioning purpose, with E 2 -E 1 -P-L 1 -L 2  points closer to the peak point for fine peak identification; and a second number Q of auxiliary tracking channels AT j , j=0 . . . Q−1, arranged in a number M of monitor channels PL 0  . . . PL M-1 , which are used for spoofing detection. Each monitor channel PL k , k=0 . . . M−1, thus includes a respective set or pool of auxiliary tracking channels AT j  linked to a specific tracking channel TRK i , i.e., a master tracking channel, among the N standard tracking channels TRK i  to be monitored in order to check for spoofing attack on such master tracking channel TRK ii . 
     The auxiliary tracking channel AT j  has substantially the same architecture, components and circuit topology, of the tracking channel TRK i  shown in  FIG.  2   , receives the same received signal I T , Q T  of the tracking channel TRK i  for the monitoring of which are used, and operates with the same Pseudo Random Noise sequence PS which is distinctive of the satellite signal s i  on which the tracking channel TRK i  operates. The only difference is that the GNSS PRN delayed sequence generator  24  outputs replica signals, very early E 2 ′, early E 1 ′, punctual P′, late L 1 ′, very late L 2 ′, which are spaced one with respect to the other of a delay value D′, i.e., an auxiliary or second delay value, which is greater with respect to the delay value D, i.e., a standard or first delay value, between the replicas E 2 , E 1 , P, L 1 , L 2  of the master tracking channel TRK i , while the respective replicas of the auxiliary tracking channels, e.g., AT j  and AT j+1 , in the same monitoring channel PL k  monitoring such master tracking channel TRK i  are delay shifted one with respect to the other. 
     In  FIG.  5 A  is shown a diagram representing a monitor channels PL 0  associated to the standard tracking channel TRK 0  as per  FIG.  6   , such channels being an example of generic channels, PL k , TRK i . 
     The diagram of  FIG.  5 A  shows the correlation amplitude versus the number of points np, the number of points np being the index of a correlation point in the series of correlation point, arranged on the abscissa according to the phase code τ, as also indicated in  FIG.  4 A . Thus, monitor channels PL k  have a greater number of points, e.g., 10 or 15 correlation points instead of just 5, with respect to the standard tracking channels TRK i , obtained allocating a plurality of auxiliary tracking channels AT j , e.g., two or three auxiliary tracking channels AT j , in parallel to obtain a wider delay line over which detect autocorrelation shape anomalies. In  FIG.  5 A  it is shown a monitor channel PL 0 , in continuous line, with 10 points, that is implemented, in the exemplary case, by the auxiliary channels AT 0  and AT 1 , which correlation curves are represented by a dotted line and dashed line respectively. A dashed window around such points indicates the monitor channel PL 0 , with 10 points which are spaced with a wider maximum, i.e., very early-very late, time spacing SM′ 0  or SM′ 1  associated to the replicas E 2 ′ 0 , L 2 ′ 0 , E 1 ′ 0 , L 1 ′ 0 , P′ 0  for the centered auxiliary channel AT 0  and E 2 ′ 1 , L 2 ′ 1 , E 1 ′ 1 , L 1 ′ 1 , P′ 1  for the shifted auxiliary channel AT 1  while a smaller dashed window around the correlation peak indicates the standard tracking channel TRK 0  with standard replicas E 2 , E 1 , P, L 1 , L 2  with a time spacing SM, smaller than the wider maximum delay or time spacing SM′ 0  or SM′ 1 . Thus, a delay D′ between the replicas of the auxiliary channels, originating phase code spacing SM′ 0  or SM′ 1 , may be for instance of a 8/16 of the chip frequency f chip  against a 1/16 of the chip frequency f chip  which may be the delay D between the replicas used in the standard tracking channels TRK i . 
     The solution here described provides that the tracking channels TRK i  are investigated for spoofing periodically and the selection of the tracking channels TRK i  to check for spoofing may be performed according to the noisiness status as recorded by the noise parameter, in one embodiment a DDM5 indicator value better described in the following. 
     Satellites, i.e., tracking channels TRK i , with the worst noisiness status, e.g., DDM5 indication, are replicated in a respective monitor structure PL k  and a wider autocorrelation analysis, i.e., on the wider phase code spacing SM′, is executed for them. 
     For instance, a number M of 8 monitoring channels PL k  each including two or three auxiliary tracking channels AT j  may be allocated to check up to 8 spoofed satellites, i.e., 8 tracking channels TRK i  in the same time. Thus, the total number of tracking channels is NS+Q, which may, in case of two auxiliary channels for each monitoring channel, result in providing at least 24 tracking channels, i.e., NS+M*2. In the example, there are 64 tracking channels, of which a number NS of 48 are allocated to standard tracking channels and Q=16 auxiliary channels AT j  are used to monitor M=8(×2) of them. This allocation is flexible and software configurable. 
     Also, as mentioned a timed routine may be performed which updates the allocation of the monitoring channels PL k  introducing new satellites in the monitor structure whereas their noise parameter DDM5 is worse, i.e., greater, than the one of tracking channel tracking a satellite already under test (continuous monitor update). 
     Pool monitoring is thus designed to be robust through reacquisition (e.g., short obscuration induced by malicious attacker). 
     In  FIG.  7 A  the upper diagram represents by way of example the overall monitor channel PL 0  correlation amplitude shape, with 10 points, that is implemented, in the exemplary case, by the auxiliary channels AT 0  and AT 1  correlation amplitudes which are represented in the lower diagram of  FIG.  7 B  and have each 5 points. Both diagrams have number of points np as abscissa, like in  FIG.  5   . In the lower diagram auxiliary channels AT 0  and AT 1  are represented aligned with respect to their index points np, which go from 1 to 5. They correspond to the correlation points 1-3-5-7-9 and 2-4-6-8-10 respectively of the monitoring channel correlation curve in  FIG.  7 A . 
     Both auxiliary channels AT 0  and AT 1  have their peak logically set to be identical to the tracking channel, e.g., TRK 0 , to which are associated, however for the shifted auxiliary channel AT 1  the peak is delay shifted, of a delay Δ, i.e., a shift delay or third delay, as shown in  FIG.  5 B , with respect to the auxiliary channel AT 0 , which is shown instead in  FIG.  5 C , to allow a complete reconstruction over ten points and avoid wasting a correlation point on the peak which is already obtained by the other auxiliary channel AT 0 . Shift delay Δ, which in  FIG.  5    is represented as phase code, is implemented as a time shift between the corresponding replicas of the auxiliary channels, and in the example may be equal to the auxiliary delay D′, e.g., 4/16 of the chip frequency, in order to have equally spaced correlation points over the total or maximum spacing SM′. 
     Thus, in  FIGS.  5 B and  5 C  it can be observed that the peak of the shifted auxiliary channel AT 1 , for prompt replica P′ 1 , is delayed by shift delay Δ with respect to the peak at the prompt replica P of the standard tracking channel TRK i . The peak of the centered auxiliary channel AT 0  for prompt replica P′ 0  is on the peak at the prompt replica P of the standard tracking channel TRK i . 
     The early and late replica of both auxiliary channels AT 0  and AT 1  are space 2Δ apart from their respective prompt replicas, while their very early and very late replicas are 4Δ apart from their respective prompt replicas. It may be noted that the correlation point of the very late replica L 2 ′ 1  is out of the shape. 
     Shift delay Δ is in the example 4/16Fchip so that the correlation powers of very early and very late replicas are substantially zero, i.e., the spacing SM′ is [+1chip, −1chip]. 
     When a satellite signal s i  is monitored by a monitoring channel PL k  a quality indicator is computed on the amplitude values of the monitoring channel PL k  in order to verify whether it is under spoofing attack or not. Such quality indicator, indicated as DDM10, is a normalized “unbalance” power detector. In the case of a monitor channel, e.g., PL 0 , with two auxiliary channels AT 0  and AT 1 , the quality indicator DDM10 is:
 
 DDM 10=(( E 2′ 0   −L 2′ 0 )+( E 1′ 0   −L 1′ 0 )+( E 2′ 1   −L 1′ 1 )+( E 1′ 1   −P′   1 ))/ P′   0  
 
where subscripts 0 and 1 stands for the auxiliary channel AT 0 , centered on the correlation peak, and AT 1 , shifted of time Δ, used in  FIG.  7 B  to produce the extended overall autocorrelation shape of the monitor channel PL 0  in  FIG.  7 A . P′ 0  is the correlation power for the punctual signal for the first channel AT 0 , aligned on the correlation peak, which is used to normalize the indicator value. As mentioned E 2 ′, L 2 ′, P′, E 1 ′, L 1 ′ indicate in the formula of DD5 the correlation power for the replicas indicated by the same reference.
 
     In other words, in  FIG.  7 B  which represents a situation without spoofing, the quality indicator DDM 10 is a sum of the differences between the power of the replicas having nominally the same values in each auxiliary channel, in particular with respect to the nominal tracked peak point. 
     In nominal conditions the DDM10 discriminator output value is zero. 
     In  FIG.  8 A,  8 B,  8 C  are shown the auxiliary channels AT 0  and AT 1  correlation amplitudes plotted verso the points NP, like in  FIG.  7 B , in case of a spoofing signal. It is 
     In  FIG.  8 A , a time t=0 s, the auxiliary channels AT 0  and AT 1  correlation amplitudes are both symmetric. There is no spoofing or the spoofing signal is weaker than the signal so of satellite S 0  received and tracked in the tracking channel TRK 0 . The differences between the power of the replicas having nominally the same values in each auxiliary channel in DDM10 tend to be zero. 
     In  FIG.  8 B , at time t=60 s, the symmetry starts deteriorating. The spoofed signal ss 0  with a greater power amplitude has seized the tracking channel which is thus locked on such spoofed signal ss 0 . The spoofed signal ss 0  is no longer aligned with the original satellite signal, thus the tails to the left are unbalanced with respect to the tails to the right, thus the differences between the power of the replicas having nominally the same values in each auxiliary channel in DDM10 start to increase. 
     In  FIG.  8 B , at time t=120 s, the symmetry is completely destroyed. The spoofed signal ss 0  with a greater amplitude controls the main peak, while the original weaker satellite signal determines an increase on the left tail, which determines in its turn a remarkable increase in the differences between the power of the replicas having nominally the same values, i.e., to the left and right of the peak, in each auxiliary channel. 
       FIG.  9 A  shows a diagram representing the DDM10 values in time t for a spoofed monitoring channel PL 0 . 
     As it can be seen for the DDM10 is above a spoof detection threshold ST, in particular for a spoof detection time td. 
       FIG.  9 B  shows a diagram representing the DDM10 values in time t for a not spoofed monitoring channel PL 0 . 
     The value of the spoof detection threshold ST is set by statistical analysis in no attack condition, as well as the spoof detection time td. The latter is the time above threshold after which a spoofing signal is detected, in order to avoid false alarms. In variant embodiments this time could be also zero, i.e., a spoofing signal is considered detected as soon as DDM10 for a monitored channel is above threshold a spoofing attack is signaled out. 
     Thus, anomalies on extended correlation shaping from monitor channels may be signaled out on NMEA/RTCM 3 to indicate the attack is ongoing on the constellation. 
     In an embodiment, upon spoofing detection, measurements affected by spoofing are gated and not provided outside to avoid pollution. 
     Additionally, detection of anomalies on multipoint shaping can trigger the adoption of a silent out of chip parallel continuous tracking trial (on a further extra channel) setting the prompt of such extra channel far from the main peak currently being tracked and potentially affected by the spoofer. 
     Also, it can be used the spatial separation between the spoofed peak measurement and the predicted satellite position estimation to discard the spoofing signal and reacquire on the genuine original satellite signal when the two quantities are well separated, (next slide scheme). 
     This necessitates of a complete genuine versus spoofer spatial identification (for instance greater than 300 m separation for the GPS case) to have the two autocorrelation function separated. 
     This is intended as a mechanism to recover (and re-lock) to the genuine satellite signal as soon as the spoofed prompt is far enough and the action of the spoofer is established and in place. 
     It relies on a stable and parallel double peak independent recognition by code separation to continue positioning on the right tracking by excluding the spoofer tracking, as also discussed with reference to  FIG.  11    in the following. 
     Identification of the genuine satellite signal vs. spoofed signal can be done by residual analysis and/or relying on another constellation position fix. 
     In  FIG.  10    it is shown a flow diagram representing an embodiment of a method  400  for detecting a spoofing signal in a GNSS receiver  100  operation of detection of a spoofing signal in a GNSS receiver  100 , comprising an operation  410  of receiving at least a satellite signal s i  in the constellation signals s 0  . . . s NS-1 , followed by acquiring  420  such satellite signal s i  as received signal I T ,Q T  in the acquisition module  4 . 
     Then an operation  430  of tracking the at least a satellite signal s i  is performed, which includes operating with a receiver comprising a set of tracking channels in the tracking module  5 ′ comprising a first subset NS of standard tracking channels TRK i  operating with a set of replicas spaced of a first delay value D and a second subset Q of auxiliary channels AT j  spaced of a second time delay D′ value greater than the first delay value D. As mentioned, this may include providing a tracking module with NS+Q hardware tracking channels like the one described with reference to  FIG.  2   , of which NS are used to track corresponding satellite signals and Q are configured, e.g., via software, to operate as auxiliary channels with respect to one or more of the standard channels in the first subset. As already indicated NS+Q may be 64, NS=48 and Q=16, each pair of the Q auxiliary channels being configured, e.g., via software programming of delays, to form a respective monitoring channel operating with replicas which are spaced for a same auxiliary channel of an auxiliary delay value D′ greater than the standard delay value D and delay shifted of a shift delay Δ one with respect to the other. 
     Such tracking operation  430  includes, as shown with reference to  FIG.  2   , receiving the received signal I T , Q T  in at least one standard tracking channel TRK i  comprising a bank of correlators  25  receiving in-phase I w  and quadrature Qw versions of such received signal I T ,Q T , generating a Pseudo Random Noise sequence PS at a code frequency Fchip set by a code Numerical Controlled Oscillator  32  comprised in the standard tracking channel TRK i  determining a code rate, performing a GNSS Pseudo Random Noise delayed sequence generation, including generating, on the basis of the Pseudo Random Noise sequence PS received from the GNSS Pseudo Random Noise sequence generator  23 , a set of replicas of the Pseudo Random Noise sequence PS comprising at least one punctual P, one early E 1  and one delayed L 1  replica of the Pseudo Random Noise sequence PS, correlating the received signal I T , Q T  with each replica in the set of replicas of the Pseudo Random Noise sequence PS to obtain amplitude correlation values. 
     The tracking operation  430  of the at least a satellite signal s i  provides its output, as the same output of tracking module  5  in  FIG.  1   , to an operation  440  of computing user&#39;s position, velocity and time, which for instance comprises the sequence of operations performed by modules  6 - 11  in  FIG.  1   . In other words, operations  430  and  440  implement the standard operations of receiver  100 . 
     Then the method here described includes performing in parallel with the tracking operation  430  an operation  500  of monitoring at least a tracking channel TRK i  allocating a corresponding monitoring channel PL k  comprising a plurality of auxiliary tracking channels AT j  in the second set Q of auxiliary channels, having respective replicas E 1 ′, P1′, L 1 ′ which are delay shifted one with respect to the other, i.e., of a time or phase code delay Δ, such auxiliary tracking channels AT j  receiving the same received signal I T , Q T  of the monitored tracking channel TRK and operating with the same Pseudo Random Noise sequence PS. 
     Such monitoring operation  500  includes in the embodiment here described an operation of measuring  510  a parameter representative of the input noise, i.e., DDM5 on one or more of the tracking channels TRK. 
     Then it is performed an operation  520  of verifying if the value of the parameter representative of the input noise DDM5 is greater than a given noise threshold ST in at least one of the tracking channels TRK, In the affirmative, it is performed an operation  530  of allocating a corresponding monitoring channel PL k  comprising a plurality of auxiliary tracking channels AT in such second set Q of auxiliary channels, having respective replicas E 1 ′, P1′, L 1 ′ which are delay shifted one with respect to the other, such auxiliary tracking channels AT j  receiving the same received signal I T , Q T  of the monitored tracking channel TRK i  and operating with the same Pseudo Random Noise sequence PS. 
     Then it is performed an operation  540  of calculating a shape anomaly factor, e.g., parameter DDM10, as a function of the correlation amplitude values of the auxiliary tracking channels AT j  associated to the master tracking channel TRK i , which is followed by an operation  540  of verifying if the shape anomaly factor DDM10 is greater than a given shape anomaly threshold ST, in particular for a given spoof detection time t d . 
     In the affirmative, it is provided signaling  550  detection of a spoofed signal ss i  on the monitored tracking channel TRK i . 
     It is underlined that in variant embodiments the monitoring operation  500  may not necessarily perform the operations  510  and  520 , i.e., perform operation  530  upon the condition a measured parameter is satisfied, e.g., it can simply perform the operation  530  on all the tracking channels or on a determined subset of the tracking channels. Also, as mentioned operations  510  and  520  can be performed by polling all the tracking channels, performing allocation operation  530  according to a ranking of the tracking channels according the noise parameter value, e.g., the tracking channels TRK i , with the worst DDM5 indication are replicated in a respective monitor structure PL k . 
     As mentioned, upon signaling  550  the detection of a spoofed signal, the method in variant embodiments can provide different action, for instance an alert, e.g., NMEA/RTCM 3 message, can be send and/or the output of the tracking channel TRK i  with the spoofed signal can be gated. 
     In a preferred embodiment shown in  FIG.  10   , after signaling  550  detection of a spoofed signal ss i  on the monitored tracking channel TRK i , a procedure  600  is performed which includes in a step  610  performing a runtime consistency check between the satellite predicted position, which is obtained by Ephemerides Extrapolation and the d Range Peak point measurement outputted by the monitored tracking channel TRK i . 
     In a step  620  is verified if a spatial separation between the spoofed signal ss i  and the original satellite signal s i  peaks is greater than a given separation distance, for instance greater than two chips, as shown in  FIG.  11   , which corresponds to 600 meters for GPS. 
     In the affirmative, it is performed an operation  560  of discarding the current tracked Peak point monitored tracking channel TRK i  which is determined by the spoofed signal ss i  and of reacquiring the satellite signal s i  on such predicted position obtained at step  610 . 
       FIG.  11    shows the by the correlation peaks of the spoofed signal ss i  and of the satellite signal s i , as a function of the number of chips, which are spaced of a separation distance SD of more than 1 chip, which in GPS corresponds to 300 meters. 
     As it can be deduced by the discussion above, the solution here described in its simplest form requires simply providing, for the tracking channel which is desired to monitor, i.e., the master tracking channel, in order to detect spoofing, to provide generation of generating a further plurality of replicas, e.g., E 2 ′, E 1 ′, P′, L 1 ′, L 2 ′ of the Pseudo Random Noise sequence PS of such master tracking channel TRK i  having a respective time spacing SM′ which is greater than the given time spacing SM on which operates the set of replicas E 2 , E 1 , P, L 1 , L 2  used for standard tracking, then correlating the received signal, e.g., I w , Q w , of the master tracking channel TRK i  with each replica in such further plurality of replicas of the Pseudo Random Noise sequence PS to obtain further amplitude correlation values, then calculating, e.g., operation  540 , a shape anomaly factor DDM10 as a function of the further correlation amplitude values determined by the further plurality of replicas E 2 ′, E 1 ′, P′, L 1 ′, L 2 ′, verify, e.g., operation  550 , if the shape anomaly factor DDM10 is greater than a given shape anomaly threshold, ST, in the affirmative, signaling,  560 , detection of a spoofed signal ss i  on such monitored or master tracking channel TRK i . 
     This is preferably performed by providing auxiliary channels, as described in the method of  FIG.  10   , i.e., by a receiver apparatus which comprises a set of tracking channels  5 ′ comprising a first subset NS of tracking channels operating with a set of replicas spaced of the given time spacing and a second subset Q of auxiliary channels which replicas E 2 ′, E 1 ′, P′, L 1 ′, L 2 ′ are spaced of such second spacing SM′ greater than the given time spacing (SM), more in particular comprising a first subset NS of tracking channels operating with a set of replicas spaced of a first delay value D and a second subset Q of auxiliary channels spaced of a second delay value D′ greater than the first delay value D. 
     The receiver apparatus in general comprises an arrangement for detecting a spoofed signal ss i  comprising a GNSS Pseudo Random Noise sequence generator for generating a further plurality of replicas, e.g., E 2 ′, E 1 ′, P′, L 1 ′, L 2 ′ of the Pseudo Random Noise sequence PS of the master tracking channel TRK i  having a respective time spacing SM′ greater than the given time spacing SM, such arrangement being further configured to correlate the received signal I w , Q w  at least a tracking channel TRK i  with each replica in the further plurality of replicas of the Pseudo Random Noise sequence PS to obtain further amplitude correlation values, calculate 540 a shape anomaly factor DDM10 as a function of the further correlation amplitude values determined by the further plurality of replicas E 2 ′, E 1 ′, P′, L 1 ′, L 2 ′, verify  550  if the shape anomaly factor DDM10 is greater than a given shape anomaly threshold ST, in the affirmative, signal  560  detection of a spoofed signal ss i  on the monitored tracking channel TRK i . This arrangement for detecting a spoofed signal ss i  may be preferably arranged in auxiliary channels AT j  as described above replicating the architecture of the tracking channel TRK i  and operating with the same received signal I w , Q w  and Pseudo Random Noise sequence PS. In embodiments, such respective time spacing SM′ greater than the given time spacing SM is such that correlation powers of the most early and most late replicas defining such respective time spacing SM′ are substantially zero, in particular the respective spacing SM′ is [+1chip, −1chip]. 
     However, in variant embodiments, the arrangement for detecting a spoofed signal ss i , may include in the tracking channel itself both the components for the standard tracking and for the spoofing detection, i.e., a single tracking channel module including a GNSS Pseudo Random Noise sequence generator generating both the set of replicas of the Pseudo Random Noise sequence PS with a given spacing SM and the further plurality of replicas E 2 ′, E 1 ′, P′, L 1 ′, L 2 ′ having a respective time spacing SM′ greater than the given time spacing SM. Of course such single tracking channel may include corresponding banks of correlators to correlate the further plurality of replicas E 2 ′, E 1 ′, P′, L 1 ′, L 2 ′ with the received signal, as well as the block for performing calculation  540  of the DDM10 parameter and the blocks for performing verification operation  550  and alert operation  560 . For instance, such single channel may generate  15  replicas, 10 with a wider overall spacing SM′ corresponding e.g., to channels AT 0 , AT 1 , and 5, with the narrower spacing SM for performing standard tracking, as shown for instance in  FIG.  5 A . 
     As mentioned, preferably the overall covered spacing SM′ is an interval [−1/Fchip,1/Fchip] around the peak, e.g., punctual replica P, i.e., [−1 chip, +1 chip], or 2 chips wide, so that the power is zero outside. As shown in  FIG.  11   , this is the separation distance SD between the spoof peak ss i  and the genuine peak ss i  when are completely separated. 
     The solutions disclosed herein have thus significant advantages with respect to the known solutions. 
     Advantageously the solution here described does not require extra hardware to operate because the auxiliary channels are obtained by rearranging via software spare hardware tracking channels. 
     The adoption of an integrated hardware/software strategy that uses in a smart way redundant channels of the GNSS solution without raising the complexity of the system and the cost of the overall BOM (e.g., antenna diversity case). 
     Of course, without prejudice to the principle of the invention, the details of construction and the embodiments may vary widely with respect to what has been described and illustrated herein purely by way of example, without thereby departing from the scope of the present invention, as defined by the ensuing claims. 
     The receiver apparatus may send the detection alert to a host processor of an autonomous driving system or of another navigation system exploiting such GNSS receiver apparatus. 
     While this invention has been described with reference to illustrative embodiments, this description is not intended to be construed in a limiting sense. Various modifications and combinations of the illustrative embodiments, as well as other embodiments of the invention, will be apparent to persons skilled in the art upon reference to the description. It is therefore intended that the appended claims encompass any such modifications or embodiments.