Signal Processing - September 2017 - 99

formance is limited by its "pull-in" range: carrier phase changes
must be contained within this range for the PLL to produce a
meaningful estimation. Scintillation signals put stress on both
of these factors.
The signal amplitude fading and rapid phase fluctuations
due to scintillation can cause cycle slips of a GNSS receiver,
reset the carrier-smoothing filter, and consequently degrade
navigation performance. An SBAS receiver, for example, uses a
100-s time constant for the carrier smoothing filter and the noise
level of the code measurements converges to the floor level after
a couple hundred seconds of smoothing. However, the carrier

Ionospheric
Wave-Front Model

Electron density irregularities are occasionally developed inside
the ionosphere under certain conditions. Then, transionospheric
radio waves are scattered by the irregularities and interfere with
each other constructively and destructively. Consequently, GNSS
signals can experience deep and frequent signal fading and random phase fluctuation. This is what is known as ionospheric
scintillation. Solar activity follows approximately an 11-year
solar cycle, and strong ionospheric scintillation is observed more
frequently in the low-latitude (equatorial) and high-latitude
(auroral and polar) regions during a solar maximum period. The
global morphology of scintillations including the source of differences between low-latitude and high-latitude scintillations is
discussed in [15].
At high latitude, most of the observed scintillation activities
are associated with bursts of rapid carrier phase changes while
very few deep signal fadings have been reported [16], [17]. In
low-latitude and equatorial areas, concurrent prolonged periods
of signal fading and carrier-phase fluctuations occur during scintillation [8], [18]. Figure 3 contrasts the detrended carrier-phase
and signal intensity of a typical high-latitude and equatorial scintillation event. These different characteristics require contrasting
strategies in mitigation techniques.
The scintillation intensity is widely described by S 4 and v z
indices. Because the S 4 index is defined as a normalized standard deviation of detrended signal intensity, it is a measure
of amplitude variations. The v z index is the standard deviation
of detrended carrier-phase measurements, which is a measure of
phase variations. For safety-critical applications, the correlation
of deep amplitude fading across multiple satellites or frequencies
is also an important measure and a correlation coefficient for that
purpose has also been suggested [19].
The problematic weak link in GNSS receivers under scintillation condition is the carrier tracking loop, especially the carrierphase-locked loop (PLL). This is because scintillation signals
are characterized by fluctuations in amplitude, carrier phases,
and carrier frequencies. It is well known that PLL performance
is limited by two factors: noise and signal dynamics [20]. The
noise performance of a PLL dictates that it outputs larger phase
estimation errors for lower signal C/N 0 . A PLL's dynamic per-

Width

Speed

Max.
Delay
ient

Grad

Higher TEC

Ionospheric scintillation and its impact on GNSSs

(a)

EPB
Speed
Max. Depletion
Gradient

Higher TEC

conterminous United States (CONUS). Even more severe gradients caused by nighttime equatorial plasma bubbles (EPBs)
were observed in the Brazilian region during the peak of the
current solar cycle (2011-2014) by [14]. The extreme gradients
as large as 851 mm/km were estimated and fully validated in
this study. Again, if this large ionospheric spatial gradient is
undetected by the reference station, the resulting range errors
could produce vertical position errors for GBAS users of several
tens of meters when combined with the worst-case airborne satellite geometries and approach timing. An ionospheric anomaly
threat model should be developed to predict the maximum position errors that the GBAS users may suffer from this anomaly.
The detail of the threat model is discussed in the section "Signal
Processing for Ionospheric Spatial Decorrelation Monitoring
and Mitigation."

Transition
Zone

(b)

FIGURE 2. Ionospheric wave-front model (a) EPB model (b) and model
parameters of the worst events observed in mid- and low latitude. (c)
Ionospheric decorrelation observed in the midlatitude region is modeled
as a simplified linear wedge parameterized by the gradient, width, maximum delay, and ground speed of the ramp as shown in (a). Figure 2(b) illustrates EPB depletion region where plasma density is significantly lower
compared with that of the surrounding ionosphere. This sharp depletion
can cause severe ionospheric decorrelation in a relatively short distance.
The worst gradients were observed and validated in CONUS (midlatitude)
during the 20 November 2003 storm event and in the Brazilian region
(low latitude) during the 1 March 2014 EPB event.

IEEE SIGNAL PROCESSING MAGAZINE

September 2017

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