GPS Receiver Architectures and Measurements

Abstract

Although originally developed for the military, the Global
Positioning System (GPS) has proven invaluable for a multitude of
civilian applications. Each application demands specific performance
from the GPS receiver and the associated requirements often vary widely.
This paper describes the architectures and functions of civilian GPS
receivers and then focuses on performance considerations. The
fundamental receiver measurements are described and the quality of these
measurements are related to the aforementioned receiver architectures

Full text

GPS Receiver Architectures and Measurements
MICHAEL S. BRAASCH, MEMBER, IEEE, AND A. J. VAN DIERENDONCK, SENIOR MEMBER, IEEE
Invited Paper
Although originally developed for the military, the Global Po-
sitioning System (GPS) has proven invaluable for a multitude of
civilian applications. Each application demands specific perfor-
mance from the GPS receiver, and the associated requirements
often vary widely. This paper describes the architectures and
functions of civilian GPS receivers and then focuses on perfor-
mance considerations. The fundamental receiver measurements are
described and the quality of these measurements are related to the
aforementioned receiver architectures.
Keywords—Code division multiaccess, distance measurement,
global positioning system, microwave receivers, phase locked
loops, radio navigation, satellite navigation systems.
I. INTRODUCTION
Beyond its original purpose as a military “force en-
hancer,” the Global Positioning System (GPS) has proven
to be a great asset in a variety of civilian applications. Air-
craft navigation systems use GPS for more direct routing.
Surveyors achieve millimeter-level accuracy, and the same
techniques are exploited by geophysicists to monitor crustal
deformation. Automotive applications include fleet man-
agement, in-car navigation systems, and automatic position
reporting during emergency cellular phone calls. Mariners
use GPS for low-visibility harbor operations as well as for
navigation in open waters. Hand-held receivers are proving
useful to hikers, campers, and other recreational users.
The demands on GPS receiver performance are as varied
as the applications. For example, the hiker is not interested
in millimeter-level positioning, but a compact, low-weight,
long battery-life unit is highly desirable. Surveying units
may take advantage of the increased accuracy which can
be achieved by exploiting the low-level of dynamics of the
receiver.
Although the specific requirements vary significantly, the
most fundamental aspects remain unchanged. Every GPS
application ultimately involves the determination of plat-
form position, velocity, and/or time. The exact algorithms
Manuscript received June 17, 1997; revised September 1, 1998.
M. S. Braasch is with the Avionics Engineering Center, School of
Electrical Engineering and Computer Science, Ohio University, Athens,
OH 45701-2979 (e-mail: mbraasch@oucsace.cs.ohiou.edu).
A. J. Van Dierendonck is with A. J. Systems, Los Altos, CA 94024-
4925 USA (e-mail: AJVD@aol.com).
Publisher Item Identifier S 0018-9219(99)00425-9.
and implementations differ depending upon the application
but in each case the most basic measurements are the same:
user-to-satellite line-of-sight (LOS) range and range-rate.
Information describing the satellite position and velocity is
also required. This is transmitted to the user in the form of
binary data over the ranging signal via a spread-spectrum
communication technique [1], [2].
This paper has been structured to provide the reader
with the concepts necessary to understand the GPS receiver
architecture. We discuss how the measurements are formed
and how the various error sources affect the quality of the
data. The paper is organized as follows. Section II provides
an overview of GPS signal processing. The fundamentals
of spread spectrum are reviewed briefly followed by a
conceptual description of the range and range-rate measure-
ment process. Section III provides a functional description
of the GPS receiver. This includes consideration of the
front-end, downconversion, digitization, and baseband pro-
cessing. The fundamental measurements are described and
common variants of the generic receiver architecture are
outlined. In Section IV, receiver performance is discussed.
The impact of various architectures on measurement ac-
curacy is highlighted along with the issues of data rates,
latencies, and interference tolerance. Section V summarizes
the paper and draws some general conclusions.
II. GPS S
IGNAL PROCESSING
Although providing position, velocity, and time is the
ultimate goal of GPS, when considered as a sensor, the
receiver’s primary tasks are measurement of range and
range-rate and demodulation of the navigation data. The
navigation data are the 50-bits/s data stream modulated
onto the GPS signal. The navigation data contain the
satellite clock and orbital parameters which are used in
the computation of user position. The GPS signal format
is known as direct sequence spread spectrum [1], [2]. More
details on spread spectrum will be given in Section II-A.
The focus of this paper is on the process of exploiting the
GPS spread-spectrum signal in order to determine range
and range-rate. First, a brief review of spread spectrum
fundamentals is given. This is followed by a conceptual
0018–9219/99$10.00  1999 IEEE
48 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999

(a)
(b)
Fig. 1. (a) Simplified BPSK DSSS transmitter block diagram.
Points (a), (b), (c), and (d) correspond to the signals given by
the same letters in Fig. 2. (b) Simplified BPSK DSSS receiver
block diagram. Mixing of the locally generated carrier brings the
signal down to baseband. Mixing of the locally generated prn code
plus the subsequent integration together act as a correlation
function.
description of how the GPS spread-spectrum signal is
exploited to determine range and range-rate.
A. Spread-Spectrum Fundamentals
A spread-spectrum system [1], [2] typically is distin-
guished by the following three characteristics: 1) the data
are modulated onto the carrier such that the transmitted
signal has a larger (and usually much larger) bandwidth
than the information rate of the data, hence the name
“spread spectrum”; 2) a deterministic signal, known a priori
to the receiver, is used by the transmitter to modulate
the information signal and spread the spectrum of the
transmitted signal; and 3) the receiver cross correlates the
received signal with a copy of the deterministic signal in the
process of demodulating the data. By so doing, the receiver
can recover the transmitted data.
The type of spread spectrum employed by GPS is known
as binary phase shift keying direct sequence spread spec-
trum (BPSK DSSS). The term “direct sequence” is used
when the spreading of the spectrum is accomplished by
phase modulation of the carrier. BPSK is the simplest form
of phase modulation where the carrier is instantaneously
phase shifted by 180
at the time of a bit change.
Consider the simplified block diagrams of a BPSK DSSS
transmitter and coherent receiver depicted in Fig. 1(a) and
(b). The binary data in the form of analog voltages either at
1or 1 is input at a rate of bits/s. The modulation
of the binary data onto the carrier may be considered as a
simple mixing operation; the same is true for the modulation
of the spreading code which increases the bandwidth of the
transmitted signal by a factor of
, where
and is the spreading code rate. Fig. 2 provides time
and frequency plots of the signals corresponding to points
(a), (b), (c), and (d) in Fig. 1(a). The binary data/signal
to be transmitted is plotted in Fig. 2(a). The result of the
BPSK modulation of this data onto a carrier is plotted in
Fig. 2(b), the spreading code is given in Fig. 2(c), and the
transmitted signal is given in Fig. 2(d).
The coherent BPSK DSSS receiver [Fig. 1(b)] despreads
the received signal by mixing in a copy of the spreading
code and then integrating over a data bit period
. Since
the data and spreading code have been modulated onto a
carrier, the received signal must also be downconverted
through mixing and filtering. This process leaves the bi-
nary data intact and thus, standard BPSK demodulation
techniques can be applied. The despreading procedure,
in general, is successful only if the receiver’s locally
generated copy of the spreading code is synchronized
with the spreading code component of the received signal.
Two questions thus arise. 1) How does the receiver know
that its locally generated spreading code is synchronized
(i.e., “locked”) with the incoming code? 2) How does the
receiver maintain lock?
The lock detector is formed by exploiting the correlation
properties of the spreading code. In order to appreciate the
spreading code correlation properties, first consider an infi-
nite sequence of truly random bits. Note the spreading code
“bits” are referred to as “chips.” First, the autocorrelation
function is defined as [2]
(1)
The autocorrelation of an infinite random sequence then is
given by [2]
for
otherwise (2)
where
is the lag value in units of seconds.
A truly random chip sequence is not realizable in practice,
but maximal-length sequences (
-sequences) provide a
close approximation. An
-element shift register can gen-
erate an
-sequence of length chips, where .
The periodic autocorrelation function of an m-sequence is
given by
for
for (3)
Fig. 3 depicts the autocorrelation functions for the ran-
dom and
-sequences. Spreading codes are usually formed
from one or more
-sequences. Since the spreading codes
approximate the properties of truly random sequences, they
BRAASCH AND VAN DIERENDONCK: GPS RECEIVER ARCHITECTURES 49

(a)
(b)
(c)
(d)
Fig. 2. Time and frequency plots for (a) data signal, (b) data BPSK modulated onto the carrier,
(c) spreading code, and (d) spreading code modulated onto the data modulated carrier. Signals (a),
(b), (c), and (d) are marked in Fig. 1(a) as well.
are referred to as pseudonoise (pn) or pseudorandom noise
(prn) sequences. When the locally generated code is locked
to the received code, the correlation effectively amplifies
the underlying BPSK data signal. The amplification fac-
tor is given by
, the length of the prn sequence. The
nonencrypted portion of the GPS signal employs spreading
codes known as Gold codes [3]. The Gold codes are formed
by combining two
-sequences. The result is a family
of prn codes with low cross correlation between codes.
This allows all satellites to transmit on the same carrier
frequency without incurring significant mutual interference.
The encrypted portion of the GPS signal also uses quasi-
orthogonal codes, but they are not Gold codes [4], [5].
Since each satellite is assigned a unique code, the system
is referred to as code-division multiple access (CDMA).
The spreading code lock detector may now be described.
Based on the autocorrelation function of the
-sequence,
it is apparent that the output of the integration block in the
coherent receiver of Fig. 1(b) will be small if the locally
generated code is not locked to the incoming code. On the
other hand, a relatively large value will be achieved if the
local and incoming codes are close to synchronization.
Once lock has been achieved, how is it maintained?
Consider the case where the locally generated code is one-
quarter chip early. The receiver thus is not quite locked.
The normalized output of the integrator in Fig. 1(b) would
be 3/4 rather than the maximum value of one. The same
value would have been obtained had the local code been
generated one-quarter chip late rather than early. A prn code
phase detector, also known as a discriminator function, is
required. This discriminator must have an output that is
unambiguous with respect to the sign of the local code
delay. This typically is achieved by correlating the received
signal with multiple versions of the locally generated code.
Consider the correlation function associated with a local
code purposely generated
chip early and the correlation
function with a local code
chip late, .A
discriminator function may be formed by differencing the
early and late correlation functions (see Fig. 4). Lock
may be maintained by feeding back the output of the
discriminator to the local code generator such that the
discriminator output is driven to zero. This mechanization
is referred to as the delay-lock loop (DLL).
The lock-detector, described earlier, allows the receiver
to determine if the local code is being generated within
1 chip of the received code. The initial acquisition of
a satellite signal involves two parts. One is a search over
all possible shifts of the locally generated code relative to
the received code. Second, as with any superheterodyne
receiver, is the mixing of a locally generated carrier sig-
nal with the incoming signal. The despreading and data
demodulation process is successful only if the locally
50 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999

(a)
(b)
Fig. 3. Autocorrelation functions of (a) normalized autocorrelation function of an infinite-length,
truly random chip sequence and (b) autocorrelation function of a finite-length (
chips), maximal
length sequence.
generated carrier is either frequency or phase locked to
the received carrier. Satellite and user vehicle dynamics-
induced Doppler shifts and satellite frequency reference
inaccuracies all contribute to a shift in the received carrier
frequency. Inaccuracies in the receiver frequency reference
also add uncertainty as a result of signal downconversion
in the front end. The acquisition process thus consists of a
search for both prn code shift and local carrier frequency
offset. Finally, just as a delay-lock loop is required to
maintain lock on the received prn code, a frequency-lock
loop (FLL) or phase-lock loop (PLL) is required to maintain
lock on the received carrier.
With this brief overview of spread spectrum fundamen-
tals, we may now discuss the concept of spread-spectrum
ranging.
B. The Concepts of Pseudorange, Delta Range,
and Accumulated Delta Range
This section will describe the fundamental ranging mea-
surements formed in a GPS receiver. A detailed description
of receiver operations is given in a later section.
1) Pseudorange: Consider a signal being generated and
transmitted by a GPS satellite. Through precise modulation
of the carrier, the satellite effectively time stamps the signal
as it is being transmitted. The time at which the signal
was transmitted is thus an integral part of the signal itself.
The signal transits from the satellite to the user and thus is
received at a later time. The time stamp on the signal, also
known as the time of transmission (TOT), is then decoded
by the receiver. In this simplified example, the satellite-to-
user range is given by
TOR TOT , where is
the speed of light and TOR is the time of reception of the
signal at the receiver.
The TOT is encoded onto the broadcast signal in two
parts. A coarse time stamp is included as part of the binary
data transmitted with the GPS signal. A fine adjustment
is achieved by tracking the prn code component of the
signal. The prn code is generated at a fixed, known rate.
By tracking the received prn code, the receiver is tracking
inherently the time at which the signal was transmitted,
thus TOT [16].
It is important to recognize that the range measurement
just described only works properly if the satellite and
receiver clocks are synchronized. This is never the case.
The difference between the observed TOT and TOR is thus
a function of both satellite-to-receiver range and receiver
clock offset. Specifically
TOR TOT (4)
where
is the satellite-to-user range, is the receiver
clock offset (usually referred to as the clock bias), and
is the resulting range-like observable known as the
pseudorange. In reality, the raw pseudorange measurement
also contains a satellite clock offset from GPS system
time. This can be corrected, however, using parameters
transmitted to the user via the navigation data message. As
is described more fully in [6], the process of positioning
requires pseudorange measurements to four satellites at a
minimum. The navigation solution involves the simultane-
BRAASCH AND VAN DIERENDONCK: GPS RECEIVER ARCHITECTURES 51

(a)
(b)
Fig. 4. (a) Cross-correlation functions between the received code and locally generated codes
which are
chip early and late and (b) code-phase discriminator function formed from the
difference between the correlation functions in (a).
ous solution of four unknowns: three-dimensional position
of the antenna/receiver and the receiver clock bias.
2) Delta Range and Accumulated Delta Range: Concep-
tually, the determination of range rate is straightforward.
The receiver tracks the Doppler-shifted carrier either with
an FLL or a PLL. The Doppler shift of electromagnetic
waves is given approximately by
(5)
where
is the transmitted frequency, is the received
frequency,
is LOS velocity, and is the speed of light.
Note that due to the convention used in the equation,
is negative if the transmitter-to-receiver range is increasing.
From (5), LOS velocity is given by
(6)
and in terms of the Doppler shift
(7)
Finally, the wavelength of the transmitted carrier is given
by
, thus
(8)
Thus, average LOS velocity may be formed by simply
counting the number of Doppler cycles over a short period
(e.g., 0.1 s) and then scaling by the wavelength and dividing
by the duration of the integration interval. In many military
receivers, an FLL is used to form the velocity estimate, and
the result is referred to as the delta-range measurement.
Alternately, accumulated delta range (i.e., change of
range) is formed if the Doppler count is kept running
continuously. By continuously running the accumulation,
(8) is being integrated. The integral of velocity is, of
course, displacement or change of range relative to the
start of the integration. At the end of a given integration
interval, a whole number of Doppler cycles will have been
counted, but usually a fraction of a cycle would remain. If
this fractional phase is also measured and included in the
accumulated delta-range observable, it is also referred to as
an “integrated Doppler” or “carrier phase” measurement.
52 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999

Fig. 5. Generic GPS receiver block diagram. 1) Antenna/Front-End: single-frequency designs pass
the L1 (1575.42-MHz) signal only; dual-frequency designs pass both the L1 and L2 (1227.6-MHz)
signals. 2) Analog-to-Digital (A/D) Converter: several types may be found in current receivers, such
as single-bit (i.e., hard limiting), multibit, and adaptive threshold types. 3) Hardware/Software Signal
Processing: single-channel designs sequentially process each satellite being tracked; multichannel
designs multiplex the A/D output into parallel channels with each channel tracking separate satellites.
4) Navigation Processing: integration of GPS and external sensor data may occur outside the GPS
receiver.
As will be shown later, the tracking accuracy of the
carrier phase measurement can be as small as a millimeter.
Unfortunately, it is only a measure of the change in satellite-
to-receiver range relative to the time the accumulation was
started. The carrier phase is thus an ambiguous measure of
range. The pseudorange is not ambiguous but the tracking
accuracy is on the order of a meter. The precision of the
carrier phase measurements can be exploited in differential
positioning as is described by Herring [7] in this issue.
In addition, the carrier phase measurements can be used
to filter the noise in the pseudorange, thereby improving
accuracy through a process known as carrier smoothing
[8], [43].
III. R
ECEIVER ARCHITECTURE OVERVIEW
Attention will now be given to the actual receiver oper-
ation. A block diagram of a generic GPS receiver is given
in Fig. 5.
A. Antenna and Preamplifier
The antenna normally is right-hand circularly polarized
to match the incoming signal, and the pattern is essentially
hemispherical in most applications. This pattern allows
tracking of satellites from zenith almost down to the hori-
zon for all azimuths. A wide variety of antennas exist.
The most common is a low-profile type consisting of
a microstrip patch element. Other types include helixes
and variants such as the quadrafilar helix. Phased arrays
originally were used exclusively by the military for jammer-
nulling. Now, however, civilian applications of the array
concept include multipath rejection [44]. Another common
multipath-reducing design is the so-called “choke ring”
in which the antenna is located in the middle of a set
of concentric electrically-conducting rings. Low-elevation
angle signals are nulled by the rings, and thus the antenna’s
gain effectively is reduced at these low angles [9].
Following the antenna, the pre-amplifier sets the noise
figure for the entire receiver system and typically has a gain
on the order of 25–40 dB. Typical low-noise amplifiers have
noise figures less than 2 dB, but the addition of preselection
filtering, burnout protection, and other associated losses
usually result in an overall noise figure of 3–4 dB.
B. Front End
The analog signal processing involves filtering, amplifi-
cation, and downconversion. Given the low power of the re-
ceived signal, out-of-band interference must be suppressed
using sharp cutoff filters. This is often accomplished using
surface acoustic wave (SAW) devices. Amplification is
straightforward in hard-limiting architectures (1-bit A/D
conversion) but multibit receivers must employ some form
of automatic gain control (AGC). Downconversion is per-
formed either in single or multiple stages. Multistage archi-
tectures allow for adequate image suppression and general
bandpass filtering with the final intermediate frequencies
(IF’s) placed close to baseband (e.g., 4 MHz). Single-stage
downconversion is becoming more prevalent, however, and
image suppression is achieved by accepting a higher IF
(e.g., 30–100 MHz). The final conversion to baseband
involves converting the IF signal to the in-phase
and
quadrature
components of the signal envelope [10].
This is accomplished by mixing the IF signal with two
tones generated at the final nominal IF but with one tone
lagging the other in phase by
radians. The output of the
two mixers are the baseband components plus the residual
Doppler. This conversion to baseband can be accomplished
either before or after A/D conversion.
BRAASCH AND VAN DIERENDONCK: GPS RECEIVER ARCHITECTURES 53

Table 1
Satellite to Receiver Link Budget
An important signal quality metric, signal-to-noise ratio
(SNR), will be discussed next. The bandwidth of the final
stage of IF filtering ranges from 2 MHz in low-end receivers
up to 20 MHz in high-performance models. The noise
power in this bandwidth can be approximated by
(9)
where
is Boltzmann’s constant ( JK ),
is the bandwidth in Hz, and is the effective noise
temperature in kelvin. The effective noise temperature is
a function of sky noise, antenna noise temperature, line
losses, receiver noise factor, and the ambient temperature.
The ambient temperature and equipment noise factors are
dominant and a typical effective noise temperature for a
GPS receiver is 513 K. This results in noise power of
approximately
138.5 dBW in a 2 MHz bandwidth (noise
density:
201.5 dBW/Hz).
The next step in the process is to determine the signal
power. The GPS link budget may be analyzed starting
with the minimum power transmitted by the satellites.
The C/A-code (at the 1575.42 MHz carrier frequency) is
transmitted at an effective level of 478.63 W (26.8 dBW)
effective isotropic radiated power (EIRP) [11], [12]. The
actual satellite antenna is composed of a phased array which
directs the signal in an approximately 29
beam toward the
Earth. The average satellite-to-user distance for near-Earth
users is approximately 2
10 m. The signal loses power
density due to spherical spreading as it propagates and the
free-space loss factor quantifies this phenomenon
free-space loss factor
(10)
where
is the carrier wavelength (0.19 m at 1575.42 MHz)
and
is the transmitter-to-receiver distance. Taking as
2
10 m, the free-space loss factor is approximately 5.73
10 or 182 dB. Atmospheric attenuation is assumed
to be approximately 2.0 dB [14] and thus the link budget
is given in Table 1 (receiving antenna is assumed to be
isotropic).
For more details on the satellite architecture and link
budget, the reader is referred to [13]. The link budget just
presented is in agreement with the GPS interface control
document [14] which specifies a minimum signal level of
160 dBW. In a 2 MHz bandwidth, then, the C/A-code
SNR is
SNR
Signal power in dB Noise power in dB
dB
A sample plot of a raw digitized GPS signal-plus-noise
is given in Fig. 6(a). The signal from a GPS antenna
was amplified, filtered, and digitized directly at RF (for
experimentation purposes) at a rate of approximately 5
MHz [15]. As expected from the SNR computation, only
white noise is distinguishable. This is further evidenced
by examining the fast Fourier transform (FFT) of the
signal [Fig. 6(b)] and noting the spectrum is fairly flat.
The nonideal passband characteristic of the front-end filters
prevents the spectrum from being perfectly flat. It is clear,
however, that the noise is dominant. The spectrum of the
GPS signals from the visible satellites is not apparent
since it lies well below the noise floor. Section III-D will
highlight the increase in SNR which results from the
baseband processing. See Fig. 9 for the FFT which results
after demodulation (i.e., postcorrelation).
C. A/D Conversion
As was mentioned earlier, both single-bit and multibit ar-
chitectures are currently in use. Most low-cost commercial
receivers employ 1-bit sampling in narrow (i.e., 2-MHz)
bandwidths. High-end receivers typically use anywhere
from 1.5-bit (i.e., three levels) to 3-bit (eight levels) sam-
pling in bandwidths ranging from 2–20 MHz. The signal
transmitted by the satellite is filtered down to a bandwidth
of 30 MHz. Although the main lobe, i.e., first-null bandwith
of the C/A-code is a mere 2 MHz wide, better signal
resolution and, subsequently, improved performance can be
achieved if the receiver processes more than just the main
lobe. More will be given on this later.
The degradation of the signal due to finite-bit quantiza-
tion is dependent upon two factors in addition to the number
of quantization levels [10]. First is the IF bandwidth. That
is, the bandwidth of the final stage of the front end. Second
is the ratio of the maximum A/D threshold to the rms
noise level. One-bit sampling is a special case which does
not depend upon the latter factor since there is only one
threshold in this case and it is at zero. The degradations are
listed in Table 2. The 1.96-dB degradation factor popularly
applied to the 1-bit case is valid only for an infinite
bandwidth signal. It should also be noted that the 3-bit
results apply only when the automatic gain control in the
front-end matches the input signal exactly to the dynamic
range of the A/D converter.
The inherent tradeoffs must be emphasized. Following
Nyquist, the required sampling rate is proportional to the
IF bandwidth. Increased cost and complexity thus accom-
pany the 3-dB improvement associated with the wideband
processing. Finally, it should be noted that A/D converters
with adaptive thresholds have been used to mitigate the
effects of narrowband interference. This will be discussed
further in a later section.
D. Baseband Signal Processing
Baseband processing of the digitized signal typically is
accomplished using a combination of dedicated hardware
(numerically controlled oscillators, correlators, accumula-
tors) and digital signal processors (DSP’s) to form the
measurements and provide feedback for acquisition and
54 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999

(a)
(b)
Fig. 6. (a) Time domain plot of raw GPS signal plus noise, sampled at approximately 5 MHz,
after front-end processing (amplification and filtering only) and (b) magnitude of the precorrelation
FFT of the GPS signals plus noise plotted in (a).
Table 2
Signal Degradation Due to Finite-Bit Quantization
in the A/D Converter
tracking. The digitized samples are mixed with in-phase
and quadrature outputs of the so-called carrier numerically
controlled oscillator (NCO) to produce the
and data
streams (Fig. 7). A feedback loop is used to ensure the NCO
matches the phase or frequency of the received signal. This
carrier NCO output also is accumulated to form the delta
range and accumulated delta-range observables.
In addition to Doppler removal, the
and samples
are mixed with early, prompt, and late versions of the
prn code and then accumulated (i.e., filtered) to form the
associated correlation values (recall the discussion on the
DLL discriminator function in Section II-A). Prior to bit
synchronization with the navigation data, the accumulation
interval (i.e., predetection integration interval) typically is
1 ms (i.e., the length, in time, of one C/A-code). After bit
synch, the accumulation interval typically is expanded to
the duration of the navigation data bit (20 ms).
The prn code tracking is maintained through a feedback
loop where the error signal is formed by differencing early
and late correlation functions. Three common discrimina-
tors are as follows [10], [16]:
Coherent
sign (11)
Early-minus-late power (noncoherent)
(12)
Dot-product (noncoherent)
(13)
where
, , , , , and are defined in Fig. 7;
sign
is the sign of the navigation message data bit. As
indicated in Fig. 7,
, and denote correlation with
early, late, and prompt versions of the locally generated
prn code. The three discriminator functions are plotted in
Fig. 8.
The discriminator output is formed in the microprocessor
and then filtered and scaled before being fed back to
the code NCO (Fig. 7). Similarly, the
’s and ’s are
processed in the software PLL or FLL to demodulate the
navigation data bits and provide feedback to the carrier
NCO to maintain phase or frequency lock.
Traditional PLL’s or FLL’s and BPSK data-demodulation
techniques can be applied since a positive SNR is achieved
after despreading (i.e., correlation). Recall the signal in
the front-end (i.e., after amplification and filtering) was
BRAASCH AND VAN DIERENDONCK: GPS RECEIVER ARCHITECTURES 55

Fig. 7. Generic GPS baseband signal processing block diagram.
Fig. 8. Code-phase discriminator functions for three common DLL implementations.
56 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999

Fig. 9. Magnitude of the postcorrelation FFT of a GPS C/A signal
present in the collected data plotted in Fig. 6(a).
completely buried in noise [Fig. 6(a) and (b)]. After being
correlated with the locally generated code, however, the
signal is despread thus occupying the bandwidth of the nav-
igation data, namely, 50 Hz. Recalling the noise equation
discussed earlier, the noise power in a 50-Hz bandwidth
is approximately 3.54
10 W( 184.5 dBW). After
correlation, and thus despreading, the SNR has increased
to: SNR
Signal power in dB Noise power in dB
157.6 ( 184.5) 26.9 dB. The increase in SNR as
a result of despreading in this case is
SNR gain
dB
Recalling the front-end data presented in Fig. 6(a) and
(b), Fig. 9 shows the computed spectra after the received
signal was correlated with the C/A-code of a visible satel-
lite [15]. The signal clearly has been raised above the
noise floor thus allowing for tracking and measurement
generation.
The SNR of spread-spectrum signals (like that of GPS) is
a function of the point in the receiver under consideration.
Precorrelation SNR’s are negative whereas postcorrelation
SNR’s are positive. It is convenient, therefore, to normalize
the SNR to a 1-Hz bandwidth and thus achieve a ratio of
signal and noise which is bandwidth-independent. Alter-
nately, this can be viewed as a density and the result is
referred to as the “carrier-to-noise density” ratio
ratio Hz (14)
where
is the straight ratio form of the SNR at a certain
point in the receiver, say, the final IF stage, and
is the
bandwidth (in Hz) of that stage of the receiver. Usually this
quantity is converted into decibels
(SNR) dB Hz (15)
In both equations, the terms in square brackets denote the
units in which C/N
is being expressed. The SNR in a 2-
MHz bandwidth was approximately
19.1 dB (0.0123 in
straight ratio) and
26.9 dB (490) in a 50-Hz bandwidth
dB Hz (16)
It should be recognized that this is merely a nominal
figure. Received satellite signal power varies with user
antenna gain, satellite elevation angle, and satellite age [5].
Typical C/N
’s range from 35–55 dB-Hz.
The GPS broadcast signal includes a C/A-code and P(Y)-
code on the Link 1 (L1) frequency (1575.42 MHz) and a
P(Y)-code on the L2 frequency (1227.6 MHz). The C/A-
code is broadcast without encryption but the Y-code is an
encrypted version of the P-code. The P-code was broadcast
during the initial buildup of the GPS constellation, and
many civilian receivers were built to track the P-code.
However, after the full complement of satellites were in
place in the early 1990’s, the P-code was encrypted, thus
forming the Y-code, and the Y-code has been broadcast
since that time. Civilian receivers have been developed to
track the Y-code and carrier on L1 or both L1 and L2
[17]–[20]. The Y-code has been deduced to be formed
by combining the P-code with an unknown, lower-rate
(approximately 500-kHz) prn code [17]–[20]. The civilian
receivers treat the encryption code as high-rate data and
essentially correlate with the underlying P-code during the
span of each encryption prn code chip. The integration
interval thus is reduced from the duration of a navigation
data bit (1/50 s) to the duration of an encryption code
chip (1/511500 s). Without further modification, this would
result in a tremendous noise penalty relative to C/A-code
processing. However, rate-aiding from the C/A-code and
carrier can be applied to the P(Y) channels allowing for
significant narrowing of the tracking loop bandwidths and
thus a minimization of the noise penalty.
IV. P
ERFORMANCE CONSIDERATIONS
As indicated in Section I, receiver architectures vary
significantly depending upon the intended application. This
section will highlight the tradeoffs among the various
architectures.
A. Acquisition
The process of acquiring the satellite signals involves
multiple steps. Simultaneous searches of frequency and
code offset are required followed by data bit synchro-
nization, frame synchronization, and finally ephemeris and
satellite clock data collection. This process is required for
each satellite to be tracked. Multichannel architectures have
dedicated hardware channels for each satellite and thus
can perform the satellite searches in parallel. Although no
longer in production, sequencing receivers are still in use
today. Most are first-generation low-cost units. Sequencing
receivers use temporal multiplexing in order to track more
satellites than the number of available hardware channels.
Such receivers are thus slower in the acquisition process.
Acquisition times range from under 1 min up to 20 min
depending upon the number of hardware channels available,
the algorithms employed, and the signal/noise conditions.
Reacquisition is a related issue. This is the case where the
receiver acquired the satellites but has lost lock temporarily.
Short reacquisition times (i.e., on the order of seconds
BRAASCH AND VAN DIERENDONCK: GPS RECEIVER ARCHITECTURES 57

or less) are especially critical in land-vehicle applications.
In densely populated areas it is not uncommon to have
more than 50% of the sky blocked by buildings. Even in
less populated areas, trees and terrain can block satellites.
Provided the blockage is on the order of a few seconds,
modern receivers generally can reacquire in less than 15 s.
The key parameter here is the maximum Doppler/receiver-
clock uncertainty which the receiver can experience without
having to revert to full acquisition mode. Doppler un-
certainty is primarily a function of the dynamics of the
platform on which the receiver/antenna is mounted since
the satellite dynamics are known through the navigation
data message. The receiver clock uncertainty (i.e., variation
in clock frequency) is a function of the clock type and
the environment (temperature, shock, vibration). High-end
GPS receivers typically employ temperature-compensated
crystal oscillators.
B. Tracking Accuracy
Measurement accuracy is limited by a variety of error
sources. Most of the error sources have to do with the
satellite or propagation medium and thus are not under the
control of the receiver. Among these are satellite clock
and ephemeris errors and atmospheric delays. However,
sensitivity to thermal noise, interference, and multipath is
highly dependent upon receiver architecture. Furthermore,
the fact that these error sources are independent between
spatially separated receivers makes them the dominant error
sources in high precision differential applications [6].
1) Noise Performance: Closed-form expressions for
DLL tracking error due to thermal noise have been derived
under the assumption of infinite signal bandwidth [21]. We
will consider this case first and then extend the results to
account for the effects of finite bandwidth. For the three
discriminators described earlier, the thermal noise tracking
error variance is as follows:
Coherent
(17)
Early-minus-late power
(18)
Dot-product
(19)
where
is the tracking error variance in units of prn chips
squared,
is the code tracking loop bandwidth in Hz, is
the early-to-late correlator spacing normalized with respect
to one chip (
is thus dimensionless and, for example, is
equal to 0.5 if the early-to-late correlator spacing is 1/2
chip), C/N
is the carrier-to-noise value in units of ratio-
Hz, and
is the predetection integration interval in units
of seconds. As mentioned earlier, for GPS the predetection
(a)
(b)
Fig. 10. RMS code tracking error due to noise. The correlator
spacing, d, has been set to one (chip) and the predetection inte-
gration interval,
, has been set to 20 ms. In (a), the tracking
loop bandwidth has been set to 4 Hz. At low C/N
(i.e., below
35 dB-Hz), the coherent discriminator results are worse than are
shown here due to excessive navigation bit errors. This portion
(
35 dB-Hz) of the coherent plot is shown here for comparison
purposes only. In (b), the coherent loop performance is plotted for
three different tracking loop bandwidths.
integration interval is usually the period of a navigation
data bit: 1/50 s. The term in brackets is the so-called
“squaring loss” inherent in noncoherent DLL’s. A plot of
tracking error versus carrier-to-noise ratio for the three
discriminators is given in Fig. 10. The rms error ranges
from approximately 0.001 chip at high C/N
to 0.1 chip
for low C/N
. With the C/A-code chip being approximately
293 m, the errors thus range from 0.3–30 m. For GPS, C/N
typically is higher than 35 dB-Hz, and so tracking errors
generally run on the lower end of the range.
Several points must be noted in order to interpret these
equations and plots properly. In the presence of strong
signals, all three discriminators converge to the same per-
formance. The equation for the coherent discriminator is not
valid at low carrier-to-noise ratios due to high navigation
bit error rate. Also not described in the equations are the
limits inherent in decreased correlator spacing. Although
the equations indicate that tracking error tends to zero with
decreasing correlator spacing, this is not actually true. The
critical point is that the equations assume infinite signal
bandwidth. In reality, the signal broadcast from the GPS
satellite is limited approximately to a 30-MHz two-sided
58 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999

Fig. 11. RMS carrier-phase tracking error due to noise for three
different carrier tracking loop bandwidths. The predetection inte-
gration interval
has been set to 20 ms.
bandwidth, and this is usually further reduced through
receiver front-end filtering.
Although closed-form expressions do not exist, Van Nee
[22] has determined the limitations inherent in the finite-
bandwidth signals. The primary limitation is a bound in
the noise reduction achieved with decreasing correlator
spacing. Van Nee has defined a noise reduction factor as
the ratio of the rms tracking error for infinite bandwidth
and one-chip correlator spacing to that of the rms error
for finite bandwidth and arbitrary correlator spacing less
than or equal to one chip. It has been shown that for a
receiver front-end bandwidth of
, the noise reduction
factor converges for correlator spacings of
or less (
is the prn chipping period and thus is equal to
times the first-null bandwidth). For example, consider a
GPS receiver with a front-end bandwidth of approximately
8 MHz. This is approximately eight times
,
[s]. The aforementioned parameter is thus
equal to eight. As a result, maximum noise reduction is
achieved for all correlator spacings of 1/8 chip or less.
For this particular case, numerical evaluation shows the
noise reduction factor to be approximately 7 [22]. This 1/8
chip “narrow correlator” receiver architecture thus achieves
a factor of seven reduction in noise over the infinite
bandwidth, one-chip correlator receiver.
Turning attention now to the carrier tracking loop, the
PLL is implemented in the form of a Costas loop and the
tracking error variance can be approximated by [10], [16]
(20)
where
is given in radians-squared, B is the carrier
tracking loop bandwidth in Hz, C/N
is the carrier-to-noise
value in ratio-Hz, and
is the predetection integration
interval in seconds. A plot of the rms tracking error
as a function of carrier-to-noise ratio for several loop
bandwidths is given in Fig. 11. In the range of C/N
given
(40–55 dB-Hz), the rms tracking error ranges from 3
down
to 0.5
. For the L1 carrier (wavelength is approximately
0.19 m), the error thus ranges from 1.6 mm down to
0.3 mm.
The tracking error thus is directly proportional to the loop
bandwidth and inversely proportional to the signal strength
and predetection integration interval. For the nominal range
of carrier-to-noise ratios, 35 dB-Hz and above, the sec-
ond term in parentheses, known as the squaring loss, is
negligible. It is important to recognize the tracking error
expression is valid regardless of the tracking loop order so
long as the loop gain is small enough not to cause stability
problems. The choice of loop order is driven by dynamics,
not noise performance.
After analyzing the tracking error equations, one might
be tempted to improve code noise performance by nar-
rowing the loop bandwidth. However, there is a price
to pay and that price is dynamic performance. In the
absence of any kind of aiding, receivers which experience
significant accelerations, such as aircraft, must employ
wider bandwidths and/or higher order tracking loops than
stationary receivers, such as surveying units. In addition,
local oscillator phase noise limits the lower bound on
tracking loop bandwidth even for stationary receivers. For
GPS, unaided code tracking loop bandwidths typically are
on the order of a few Hertz and unaided carrier tracking
loop bandwidths are in the range of 5–15 Hz.
One way to improve both noise and dynamic track-
ing performance simultaneously in code tracking loops
is to employ rate-aiding. Since the carrier-tracking accu-
racy is excellent even at wide bandwidths (see Fig. 11),
its velocity measurements can be used to aid the code-
tracking loop. This can be performed in two ways. The
first way is to make the aiding an integral part of the code
loop in which case it is referred to as carrier-aiding. If
the carrier loop measurements are used to aid the code
loop, the code tracking loop bandwidth may be narrowed
without suffering significant lags during signal dynamics.
The second technique is to use the integrated Doppler
measurements as a trajectory reference against which to
smooth the noise in the pseudo-range measurements. This
technique is referred to as carrier-smoothing [8]. Although
the aforementioned has focused on aiding the code loop,
it is also possible to derive similar benefits in the carrier
loop. Rate aiding of the carrier loop can be achieved
through integration of the GPS receiver with an inertial
measurement unit.
In accord with sampling theory, the maximum indepen-
dent sampling rate is twice the tracking loop bandwidth.
As mentioned earlier, unaided code tracking loops have
bandwidths on the order of 1–4 Hz depending upon the
expected dynamics. This gives rise to maximum sampling
rates of 2–8 Hz. GPS PLL’s, however, generally operate
with tracking loop bandwidths in the range of 5–15 Hz,
thus providing data rates of 10–30 Hz. Most receivers,
however, provide outputs ranging from 1–10 Hz. This
addresses the need (in current receivers) to minimize the
burden on the internal bus structure and the processor
throughput capability. Data latency is a related issue which
is also governed primarily by internal communication and
processor capabilities. Typical latencies range from 200 ms
to 2 s.
BRAASCH AND VAN DIERENDONCK: GPS RECEIVER ARCHITECTURES 59

2) Interference Performance: Although interference, typ-
ically in the form of jamming, is of primary concern to the
military user, civil users are also impacted by interference.
The primary civil concern is that of unintentional inter-
ference as a result of harmonics, spurious emissions, or
intermodulation products from non-GPS transmitters which
fall in the GPS bands. Safety critical applications such as
civil aviation have spurred a variety of tests and theoretical
analyses [23]–[25]. The majority of high level interference
has been observed on the European continent [26]. In
particular, amateur radio digital data transmitters (packet-
radio transmitters or digipeaters) operating at approximately
1240 MHz have been observed to cause complete blockage
of the L2 signal [26].
The exact impact of interference is dependent both on
the interference type and the GPS receiver architecture.
Both subjects are treated theoretically in [27] and [28].
Narrowband interference resistance is inherent in direct
sequence spread spectrum systems. A typical GPS C/A-
code receiver can tolerate a narrow band interferer that is
approximately 40 dB stronger than the GPS signal. This is
referred to as interference-to-signal ratio (I/S) or jammer-to-
signal ratio (J/S). The key weakness with the C/A-code is its
relatively short period. With a period of 1 ms, the C/A-code
spectrum is not continuous, but rather it is a line spectrum.
If a narrowband interferer jams a strong C/A-code line,
additional degradation will result.
As Ward [28] has pointed out, a receiver’s ability to
tolerate I/S equal to 40 dB sounds impressive until the
absolute interference power is calculated. With a minimum
received signal power of approximately
160 dBW, the
interference need only be stronger than 1 pW to disable the
receiver. In field tests, 1-W jammers have been shown to
disable civilian receivers over more than a 20-km radius.
Recent bench tests have shown that high-end receivers can
experience position errors on the order of ten meters just
prior to loss of lock when operating in the presence of
broadband noise [25]. For the sake of completeness, it
should be pointed out that there was no loss of integrity
in this bench test. The C/N
computed by the receiver
accurately reflected the strong noise environment.
Narrowband filtering in the front end is commonly em-
ployed to reduce the receiver’s susceptibility to out-of-band
interference. The most dramatic impact of receiver design
on interference performance, however, can be observed
when narrow band interference is considered.
The key issue is the fact that a sinusoid spends very
little time near zero. Instead, it spends most of its time
near its peak positive and negative values. Now consider a
GPS receiver with a 1-bit sampling architecture. As long
as the sinusoidal interferer is stronger than the GPS signal,
the 1-bit A/D converter will be captured by the sinusoid.
In other words, the GPS signal is dithering the sinusoid
but the A/D converter cannot observe this. On the other
hand, in a multibit architecture with adaptive thresholds,
the thresholds can be set close to the peak positive and
negative received signal values and thus can observe the
GPS-induced dither [27], [29].
3) Multipath Performance: As with interference, multi-
path is generated external to the receiver, yet the receiver
architecture has a significant impact on performance. The
primary multipath parameters are strength, delay, phase,
and phase-rate, all measured relative to the direct signal.
The relative multipath strength is denoted as the multipath-
to-direct ratio (M/D). As with thermal noise, analysis of
the code and carrier tracking loops yield the relationship
between the multipath parameters and the resulting mea-
surement errors [22], [30]–[36], [43].
Conceptually, the effect of multipath on the pseudorange
and carrier-phase measurements may be understood as
follows. First, consider the discriminator functions plotted
in Fig. 12 (recall Fig. 4 shows how the discriminator is
formed from the early and late correlation functions).
Fig. 12(a) shows a coherent discriminator for a received
signal consisting of the direct ray only. Now consider a
single multipath ray which is in-phase and distorting the
direct signal. The resulting discriminator function is plotted
in Fig. 12(b). Analytically, this may be considered as the
sum of two discriminator components. One is associated
with the direct signal and the other is associated with
the multipath [Fig. 12(c)]. As discussed earlier, the code
tracking loop adjusts the locally generated code such that
the discriminator output is forced to zero. In the presence of
multipath [Fig. 12(b)], however, the zero-crossing is shifted
from the correct position [Fig. 12(a)]. This results in the
local code lagging or leading the received direct code. The
pseudorange multipath error is thus given by the amount of
lag or lead in the local code.
In the presence of a single multipath ray, the pseudorange
multipath error envelope is plotted in Fig. 13 [32]. The
initial slope is a function of multipath amplitude and delay
only. This initial slope thus is independent of correlator
spacing and prn chipping rate. If the multipath delay is
“short,” the resulting pseudorange error will be the same for
C/A-code or P-code. Another item to note is the presence
of error at long delays resulting from the nonzero prn code
autocorrelation sidelobes.
For multipath weaker than the direct signal and a corre-
lator spacing of one chip, the maximum error is one-half
chip. This is approximately 147 m for the C/A-code and
14.7 m for the P-code. As was the case for the noise
equations, the multipath theory assumes infinite GPS signal
bandwidth. Finite bandwidth effects can be handled through
simulation and the results are similar to those of the infinite
bandwidth case [21], [34]. The finite bandwidth effects
are most apparent at medium and long delays with errors
increasing by 20% to 40% over the infinite bandwidth case.
For short delay multipath, the finite bandwidth effects are
much less significant.
Similar to the noise case, multipath performance is also
improved with narrow correlator architectures. The peak
error (Fig. 13) is scaled by the correlator spacing
.It
follows, then, that a narrow correlator receiver with
would experience a maximum pseudorange error of
14.7 m, whereas a standard correlator (
) receiver
would experience 147 m of error. Since the error given
60 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999

(a)
(b)
(c)
Fig. 12. Discriminator functions associated with (a) the direct signal only, (b) direct plus multipath
signal, and (c) the direct-only component and the multipath-only component.
Fig. 13. Theoretical pseudorange multipath error envelope for the case of infinite signal bandwidth.
The upper curve represents the case where the multipath is in-phase with the direct signal. The lower
curve represents the out-of-phase case. In general, the actual multipath error will vary between these
two extremes. The multipath-to-direct signal strength ratio is given by
and is the early-to-late
correlator spacing in units of prn chips.
is assumed to be less than one.
BRAASCH AND VAN DIERENDONCK: GPS RECEIVER ARCHITECTURES 61

in Fig. 13 is in units of prn chips, one may conclude
that P-code performance on the whole is better than for
the C/A-code. This follows since a P-code chip is 1/10
the length of a C/A-code chip. In addition, the error
envelope essentially goes to zero for delays greater than
chips since the P-code autocorrelation sidelobes
are essentially negligible. The key exception to the superior
P-code performance is in the case of short delay multipath
(i.e., multipath with delays less than 1/10 C/A-chip length).
As described in [33], all current receiver architectures have
similar multipath performance in the presence of short
delay multipath. In addition, recent developments in C/A-
code receiver technology have improved medium and long
delay multipath performance significantly. This improved
multipath performance, however, is achieved at the price
of loss of SNR and/or increased architecture complexity
[37]–[42].
The effect of multipath on the carrier phase may be
viewed most effectively through a phasor diagram (Fig. 14).
The relative phase between the direct and multipath signal
is denoted by
. The receiver cannot distinguish the
components of the distorted signal and thus must track the
composite. The phase difference between the direct and
composite signals
is the carrier-phase multipath error.
In order to determine an upper bound, it is assumed the
relative phase-rate between the direct and multipath signal
is zero. As a result, the e
time dependence relating the
phasors to the actual time-domain signals can be ignored.
The magnitudes of the direct and multipath phasors are
given by
(21)
(22)
where
is the prn code autocorrelation function as a
function of lag
is the delay of the multipath relative
to the direct, and
is the ratio of the multipath signal
strength to direct signal strength.
is sometimes referred
to as multipath-to-direct ratio (M/D). In order to derive
the equation for
, it is convenient to decompose the
multipath phasor into its in-phase (
) and quadrature
(
) components [Fig. 14(b)]. It is now apparent
arctan (23)
which may also be written
arctan (24)
The maximum possible error is
radians or one-
quarter carrier wavelength. For the GPS L1 frequency,
this amounts to approximately 4.8 cm. This extreme is not
common, however, and errors typically are less than 1 cm.
Recent developments in receiver architectures have
achieved some reduction in carrier-phase multipath
error [22], [37], [40], [42]. As with the pseudorange
improvements, the carrier-phase improvement is achieved
only for medium and long-delay multipath. Of the three
(a)
(b)
Fig. 14. Phasor diagram depicting relationship between relative
multipath strength, phase
, and resulting carrier phase error.
In (a) the composite received signal is shown to be the vector
sum of the direct plus multipath. The phase difference between the
direct and the composite is the carrier-phase multipath error
.
In (b) the multipath phasor is decomposed into its in-phase and
quadrature components for the purpose of deriving the equation
for the arctangent of
.
techniques proposed [37], [40], [42], only one has been
documented publicly [22], [37]. Theoretical performance
and field trial results have been published for the other
two but the implementation details so far have not been
made public.
To conclude this section we recall the C/A-code pseudor-
ange multipath error can approach 147 m, theoretically. As
long as the receiver is not in the vicinity of large obstacles,
however, errors of 10 m or less are far more common.
Large errors can be encountered in the urban environment,
specifically near skyscrapers. Pseudorange errors in excess
of 100 m have been measured with stationary GPS receivers
located near skyscrapers [22]. This is of particular concern
in applications such as vehicle navigation systems.
V. C
ONCLUSIONS
This paper has provided an overview of the processing
performed in a GPS receiver and the various tradeoffs
possible in the design. Currently, the cost of a GPS receiver
(not in quantity) ranges from approximately $100–$20 000.
Performance roughly parallels cost. High-end receivers are
marked by low-noise front ends, multibit A/D converters,
and higher speed digital signal processing. This, in turn,
allows for noise, multipath, and interference reduction. In
addition, high-end civilian receivers are available which
track both GPS frequencies. As more receivers are manu-
factured in high volume ASIC-based designs, it is expected
that even high performance will be available at lower prices.
As was stated in the introduction, GPS is being utilized
in a wide variety of civilian applications. For example, a
high-end survey receiver will track both GPS frequencies
through an extremely low-noise front end and narrow
carrier tracking loops. This allows for the highest precision
62 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999

possible in the carrier phase measurements. Dynamics are
not a problem for the narrow tracking loop since the
receiver will not undergo significant dynamics. In addition,
it is not uncommon for survey receivers to have data
latencies on the order of a second. Again, this is perfectly
acceptable since the receiver typically is experiencing low
dynamics and the data is not being used in real time.
The GPS receiver found in a transoceanic aircraft will
be quite different than a survey receiver. With safety-of-
life as the primary issue, reliability and availability are as
important as accuracy. The receiver must operate in a wide
variety of environmental conditions including interference.
Acceptable interference performance may require narrow-
band front-end filters, multibit adaptive A/D converters,
and subsequent complex baseband processing. Operation at
low C/N
may require noncoherent carrier and code loop
mechanizations. These loops exhibit wider hold-in ranges
but pay the price with slightly degraded tracking accuracy.
The wide variety of applications is a testimony to the
utility of the system. Receiver manufacturers have met
this challenge with an equally wide variety of receiver
architectures. Equipment buyers must be aware of the
aforementioned differences and must be careful to match
the receiver performance specification to the requirements
of the given application.
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Michael S. Braasch (Member, IEEE) received
the Ph.D. degree in electrical engineering from
Ohio University, Athens, in 1992.
He has been performing research with the
Avionics Engineering Center at Ohio University
since 1985 and has worked on a variety of
aircraft navigation systems including ILS, MLS,
VOR, Loran-C, DME, INS, and GPS. In 1993,
he served as a Visiting Scientist at the Delft
University of Technology in the Netherlands.
Since 1994, he has been an Assistant Professor
in the School of Electrical Engineering and Computer Science and a
Research Scientist with the Avionics Engineering Center, Ohio University.
He has lectured for NATO AGARD and has authored book chapters on
multipath and selective availability. Since 1995, he has directed the GPS
software radio and signal modeling research teams at Ohio University.
Dr. Braasch has supported the FAA in national and international forums
such as RTCA, the ICAO All Weather Operations Panel, and the ICAO
Obstacle Clearance Panel. In 1992, his dissertation characterizing the
effects of multipath on DGPS landing systems won the RTCA’s William
E. Jackson Award for an outstanding publication in aviation electronics.
A. J. Van Dierendonck (Senior Member, IEEE)
received the B.S.E.E. degree from South Dakota
State University, Vermillion, and the M.S.E.E.
and Ph.D. degrees from the Iowa State Univer-
sity, Iowa City.
He has 25 years of GPS experience. Currently,
he is self-employed under the name of AJ Sys-
tems and is a General Partner of GPS Silicon
Valley.
In 1993, Dr. Van Dierendonck was awarded
the Johannes Kepler Award by the Institute of
Navigation Satellite Navigation Division for outstanding contributions to
satellite navigation. In 1997, he was awarded the ION Thurlow Award for
outstanding contributions to the science of navigation.
64 PROCEEDINGS OF THE IEEE, VOL. 87, NO. 1, JANUARY 1999