To be capable of receiving and decoding the information from a satellite in a satellite positioning/navigation system, a receiver is required to carry out an acquisition process to recognize the signal in the space and correctly identify the presence of the satellite from which this signal has been received, the latter being typically affected by unspecified delay and Doppler shift.
Specifically, the acquisition and tracking system (fine acquisition) of a receiver is required to recognize the correct acquisition of a signal by carrying out comparison (correlation) operations between the input signal and a set of codes (pseudo-random sequences) that belong to the various satellites in the constellation and are locally generated by the receiver, which operations are carried out in a research domain being defined by the variables: code delay and Doppler shift.
The acquisition process generally implies calculating the correlation between the received signal and a local replica of the code available at the receiver, and an acquisition is declared when the value of a variable or test function such as a predetermined correlation function, such as the correlation energy, is higher than a preset threshold.
The performance of the acquisition strategy is traditionally assessed in terms of acquisition time, detection probability and false alarm probability and depends, inter alia, on the carrier signal-to-noise ratio C/N0.
BOC modulated signals are candidates for use in the next generation satellite navigation systems, particularly the GPS system updated edition and the innovative GALILEO system. They have reduced multiple-path distortion and potentially improved code tracking characteristics.
Disadvantageously, a BOC modulated signal has a multiple peak autocorrelation function. Due to the presence of secondary peaks, several problems arise both during the acquisition step and tracking step of codes, when prior art receivers are used, which recognize an acquisition on the basis of a threshold comparison of the signal autocorrelation function. In fact, a lock on secondary peaks is possible with non-null probability (acquisition ambiguity) and the lock on a secondary peak cannot be resolved during the tracking step.
Solutions are known in the literature, most of which are effective in ambiguity mitigation for sine BOC modulated signals, but less effective if applied to cosine BOC modulated signals.
For example, a tracking discriminator of the traditional Early Minus Late (EML) type being applied to a BOC(1,1)-modulated pseudo-random noise code and with an interval between the early replica and late replica (Early-Late interval) lower than chip time Tc has a discriminator curve (curve S) with three stable lock points, the desired one being at the x-axis point 0 and two further points at ±0.55Tc, respectively, and the latter can introduce unacceptable pseudorange errors, in the order of tens of meters.
In order to limit this problem, new acquisition and tracking algorithms have been proposed in the art, which, however, require more complex receivers.
Most of these algorithms tend to attenuate the secondary peaks of the autocorrelation function by combining, in the definition of the above-mentioned test function, the correlation function between the received signal and the local replica of the BOC modulated signal, with the correlation functions between the received signal and suitably selected auxiliary signals or waveforms. One of these waveforms is the unmodulated pseudo-random noise signal (PRN). The cross correlation function of the unmodulated pseudo-random noise signal with a BOC modulated signal has peaks proximate to the secondary peaks of the autocorrelation function of the BOC modulated signal and a lower value for perfect alignment.
One solution proposed in the literature for reducing the ambiguity, provides for carrying out a cross correlation with the relative locally generated unmodulated pseudo-random noise code.
When the cross correlation function between the received signal and the unmodulated pseudo-random noise code is combined with the autocorrelation function of the BOC modulated signal, the following test variable is definedU=|xBOC(n)|2−|xBOC/PRN(n)|2 wherein xBOC(n) is the autocorrelation function of the BOC modulated signal and xBOC/PRN(n) is the cross correlation function between the BOC modulated signal and the pseudo-random noise code.
As the BOC/PRN cross correlation function has peaks proximate to the secondary peaks of the BOC autocorrelation function and results to be of a nearly null value at the main peak of the autocorrelation function, this test variable allows for a good separation between the main peak and the secondary peaks, thus lowering the acquisition ambiguity and eliminating the stable lock points of the Early-Minus-Late (EML) discriminator approach that are arranged at Tc/2 distance from the actual lock point.
Disadvantageously, this approach requires that the operations required for calculating the tracking discriminator functions and for evaluating the BOC/PRN cross correlation function are doubled.
On the other hand, as relates to the code tracking step, the traditional approaches for consumer products are based on Early-Minus-Late algorithms or DOT algorithms.
However, it should be considered that Early-Minus-Late approaches are not capable of recovering the ideal stable lock point from a secondary lock point.
An example of this situation is illustrated in FIG. 1, where a curve S is depicted of a DOT discriminator for a sine BOC(1,1) modulated code and Early-Late interval of 0.4Tc. The correct lock point is the one in the middle, which is indicated at 0 on the X-axis, whereas the false lock points are the two lateral points, at −0.6Tc and +0.6Tc on the x-axis, respectively.
Also in these cases, several solutions have been proposed in the literature, such as the “Very Early-Very Late” or “Bump-Jumping” schemes. In this case, however, a second pair of correlators is required to be used with an interval equal to or greater than 0.5Tc, and it is required to check whether the indication lies on the correct peak or a secondary peak. The discriminator can either directly incorporate the difference of the correlator outputs or compare the correlation energy according to the EML method with that obtained according to the VEMVL method for deciding the correct tracking pitch to be forwarded to the Numerical Control Oscillator for subsequent time-adjustment.
Another approach describes a tracking scheme in which the product of the EML approach obtained using the autocorrelation function of the BOC modulated signal is combined with the product of the EML approach obtained using the cross correlation function between the BOC modulated signal and the pseudo-random noise signal, with a preset scaling factor. The curve S obtainable according to the latter approach does not have secondary stable points, but the operation range thereof is not greater than 0.4Tc.
However, increasing the operative range is desired, as major delays can be made up while the acquisition system is simultaneously allowed to consider a research time grid with a wider spacing (for example, instead of carrying out the test with the distance between subsequent delays amounting to Tc/4, a spacing of Tc/2 (or, at the most, Tc) can be used, thus reducing the calculations and time used for the signal acquisition and the initial (loose) estimate of the delay.
A further problem to be addressed is that the tracking performance of a receiver in a satellite positioning system results are severely degraded when the signal received is affected by a multiple path propagation. In this case, the discriminator curve S in the code tracking changes its shape while crossing the x-axis no longer at the origin, and thus introducing a polarization in the pseudorange measurements, thereby increasing the uncertainty in the position estimate.
Solutions have been introduced for ensuring a better rejection of multiple paths with GPS system signal, but their effectiveness still has to be proved for BOC modulated signals used in the future GALILEO positioning/navigation system.
USPTO Backgrounds
USPTO Backgrounds