The Next Generation of a Super Sensitive
GPS System
Lawrence R. Weill, Department of Mathematics, California State University, Fullerton, CA
Nobuhiro Kishimoto, Seiichiro Hirata, Magellan Systems Japan, Inc., Osaka Japan
Kevin Xinhua Chin, Galileo Positioning, Menlo Park, CA

BIOGRAPHIES
Lawrence R. Weill
Dr. Weill received B.S. and M.S. degrees inElectrical Engineering from the California Institute ofTechnology in 1960 and 1961, respectively. In 1968
he earned the M.S. Degree in Mathematics at San
Diego State University, and was awarded the Ph.D.
in Mathematics in 1974 at the University of Idaho.
He is currently Professor of Mathematics Emeritus at
California State University, Fullerton, and has
operated his own consulting firm for 25 years.
Dr. Weill is also one of the three technical foundersof Magellan Systems Corporation (now Thales
Navigation), which in 1989 produced the world’s firstlow-cost handheld GPS receiver for the consumer
market.
As an active researcher, Dr. Weill has publishednumerous papers on signal processing for GPS,radar, sonar, optical sensor, and satellite
communication systems. He has recently madesubstantial contributions to both the theoreticalfoundations and practical aspects of GPS multipath
mitigation, and to the design of high-sensitivity GPS
systems.
Nobuhiro Kishimoto
Mr. Kishimoto entered the Tokyo University of
Science in 1976, where he received a Bachelor’s
degree in Science. He also studied at the Kwansei
Gakuin University where he received a Bachelor’s
degree in Theology in 1984. Mr. Kishimoto has 3
years of experience in the development ofsemiconductor processing techniques and 16 years
in the GPS industry.

In 1988 he founded Magellan Systems Japan, Inc.,
which has long been exclusively involved in
representing the GPS OEM business, as well as
being an international distributor for a division ofThales Navigation (formerly Magellan Systems
Corporation) in the Japanese market.
In addition to marketing experience, in 1999 Mr.
Kishimoto spearheaded innovative developments inhigh-sensitivity assisted GPS receiver technology for
application to cell phone position location. Recently
he has been in charge of an advanced generation ofthis technology.
Seiichiro Hirata
Mr. Hirata graduated from Kyusyu University in
March 1966, where he studied in the Electronics
Department.
He joined the Mitsubishi Electric
Corporation in April of that year, where he wasengaged in the development of transistorized color
television receivers and served as a member of theSatellites Ground Bureau. He contributed to several
firsts in the electronics industry, including theelectronic video recorder, automated tuned carradios, GPS car navigation systems, and a highsensitivity GPS system.
In October 2003 Mr. Hirata joined Magellan Systems
Japan, Inc., where currently he is the principal
developer of the next generation super sensitiveindoor GPS system, mainly for cell phone
application, which is described in this paper.
Kevin Xinhua Chin
Dr. Chin received his B.S. degree from Beijing
Institute of Technology and the Ph.D. in Aeronautics
and Astronautics from Stanford University, where heworked on the Gravity Probe-B program.

Dr. Chin is the founder and CTO of Galileo
Positioning, an early stage venture and consultancy
specializing in GNSS receiver system design,navigation system integration, digital signal
processing,navigation
algorithms,
GNSS
applications, and location based service.
In addition, Dr. Chin has worked for the last thirteen
years at Ashtech, Inc., Magellan Systems
Corporation, and Thales Navigation, Inc. He has
held various positions as an engineer, a manager,
and most recently as director of engineering anddirector of strategic technology. He pioneered the
Ashtech RTK algorithms (PNAV), led thedevelopment team, and was directly involved in its
implementation and enhancements in four
generations of dual-band GPS receivers.
ABSTRACTThis paper describes the next generation of a supersensitive assisted GPS system for C/A codedsignals that was originally developed by Magellan
Systems Japan, Inc. in collaboration with aJapanese electric company and Thales Navigation.
The improved system is designed to provide rapid
positioning in weak signal areas, such as insidebuildings. In addition to other applications, a primary
goal is to embed the client receiver in cell phones toenable rapid location in an emergency such as a
911 call.
Proprietary techniques have beendeveloped to obtain the following improvements:
1. Low-latency time coordination between the client
receiver and the assisting base station (server) is not
required.
2. High sensitivity is maintained with a short signal
capture time and without the need to know thenavigation message bit sequence from any externalsource.
3. The local oscillator frequency offset at the client
receiver can be estimated efficiently, thus reducing
the cost of the local oscillator and eliminating theneed for an accurate frequency referencetransmitted by the server.
These and other improvements permit existing
communication systems, such as cell phone
networks, security systems, and the internet, totransmit assisting information to the client receiverwith only a simple communication interface to areference GPS receiver. No major modifications tothe communication system are required, which is asignificant advance in the state of the art of assisted
GPS systems.

Theoretical design considerations and preliminary
test results of the improved high sensitivity system
are presented in this paper.
I. INTRODUCTION
The first generation of a super sensitive GPS system
was initiated in 1999 by Magellan Systems Japan,
Inc. in collaboration with a Japanese electriccompany and Thales navigation.
The first
generation system, which was completed in 2000,
successfully demonstrated that rapid assisted GPS
positioning is possible with signal levels approaching–160 dBm, using no more than a few seconds of
captured GPS signals. Tests conducted in 2003
demonstrated that positioning was quite reliable,
even inside concrete buildings.
A key to the high performance of the first generation
system is the inclusion of the following information in
the assisting data transmitted from the base station(server) to the client receiver unit:
1 Precise frequency and timing information.
2. The sequence of navigation data bits from eachsatellite.
3. Ephemeris information for
positions of the satellites.

determiningtheThe precise frequency information is used tocalibrate the client receiver reference oscillator,
which reduces the frequency range that must be
searched to acquire satellites. The precise timing
information permits the client receiver to accurately
determine the time at which it captured the satellite
signals, so that the position of the satellites neededin the navigation solution can be established from
ephemeris data.
Optimum processing gain of a conventional GPS
receiver is limited by the maximum coherent
integration time of 20 milliseconds imposed by the
50 bps GPS biphase data modulation. In the first
generation system this limitation is overcome bysending the sequence of navigation data bits to theclient receiver.
The client receiver uses thesequence to strip the modulation from the signal,thus permitting a much longer coherent integration
time and a concomitant increase in processing gain.
Although the frequency, time, and data bit
information is useful in achieving a high level of
performance, its provision makes it difficult to sendassisting information from server to client using
existing communication systems, such as cell phonenetworks, security networks, or the internet. Thesesystems would likely need extensive modification, or
perhaps a whole new system would be necessary.
For example, the transmission of an accurate
frequency reference would require precise frequency
control in the transmitter of every tower in a cell
phone network. Transmission of accurate timing
using conventional methods could also be a problem,
due to data transmission timing uncertainties in suchnetworks.
For these reasons, a new generation of assisted
GPS positioning system, named Yokozuna, wasinitiated in 2003 to overcome these disadvantages.
II. OVERVIEW OF THE YOKOZUNA SYSTEM
A block diagram of the Yokozuna system is shown in
Figure 1. Like any assisted GPS system, theYokozuna system uses a base station, called theserver, to send information to client receivers, whichmakes it possible for these receivers to achieve
rapid positioning with very high sensitivity. The key
difference between the Yokozuna approach andmost others is that the assisting information can besent via unmodified existing communication systems.
An important aspect of the Yokozuna system is thatthe assisting information is obtained by one-way
data transmission which streams from the basestation. This data is available to all users of thesystem, even if they are operating simultaneously,
and no request for the information is required. Thisdata consists of the following:
1. Base station location
2a. Time-tagged satellite position and velocity
vectors, pseudoranges, and Doppler.
AND/OR
2b. Satellite ephemeris data
3.
Timing information using a combination of
proprietary techniques.
Time accuracy is notdegraded by unknown and variable time delays that
may exist in the server-to-client communication
system, even if these delays are very large (morethan several seconds).

The client receiver captures a short segment(typically 1-3 seconds) of received GPS signals,
processes the signals to obtain pseudoranges, andcomputes a position solution which can bepresented to the user and/or automaticallytransmitted to authorities via the user’s cell phone orother communication means. The receiver can be
activated by pressing a “panic button” or by othermeans.
The client receiver consists of an RF tuner which
also provides frequency translation to baseband, an
A/D converter, and digital processing to produce anestimate of the client location.
The digitalprocessing consists of Doppler compensation of thesatellilte signals, a proprietary process whichremoves the polarity changes due to the navigation
data message bits, correlation processing to achieve
processing gain and measure pseudorange for eachsatellite signal, and the computation of position.
Additional details of the client receiver, which might
be embedded in a cell phone, is shown in Figure 2.
The GPS signals are received by an antenna(typically a patch design) and are amplified andfrequency translated to a 4.092 MHz IF frequency by
the RF tuner. Local oscillator signals for the RF
tuner are provided by a frequency synthesizer driven
by a 16.368 MHz reference crystal oscillator. The
reference oscillator is a proprietary design which has
small frequency uncertainty in order to minimize thefrequency search range in acquiring the satellite
signals. The IF signal is bandpass-filtered andconverted to digital samples by an A/D converter.
The samples are then digitally translated to acomplex-valued (I and Q) baseband signal by twodigital multipliers. The local oscillator signals forthese multipliers are in-phase and quadrature phase
digital waveforms at 4.092 MHz, supplied by thefrequency synthesizer. The baseband I and Q
components are stored in a signal capture memory,where they are accessed for further processing.
The IF bandpass filter has a relatively small
bandwidth in order to reduce the sampling rate sothat the size of the capture memory can be madeacceptably small.

The above data can be updated at a relatively slow
rate, perhaps once every few seconds.

The signal in the capture memory is thesuperposition of all received satellite signals. Thesesignals are individually compensated for Doppler
under the control of a CPU, using Doppler data
received from the server via the communication
receiver card shown in Figure 2.

In many (but not necessarily all) applications, theclient receiver and its processing hardware andsoftware are embedded in a handheld cell phone.

Following Doppler compensation, the navigation
data bit polarity changes are removed from eachsignal by a proprietary technique, and partial

processing gain is achieved by a special techniquein the Digital Processing Block shown in Figure 2.
The remainder of the processing gain is achieved in
the Correlation Block. A peak detector finds thesignal delay corresponding to the largest correlation
value for each satellite, and the delay values areused by the Position Computation Block to computethe position of the client.
III. CONSIDERATIONS IN SYSTEM DESIGN
Fully Coherent vs Partially Coherent Processing
Because the Yokozuna system must provide very
rapid positioning, there is not enough time for theclient receiver to acquire the GPS signals andextract the satellite ephemeris information required
for a position solution. Therefore, it must be able torapidly process at most a few seconds of received
signal.
The ultimate receiver sensitivity that can beachieved is affected by the length of the signal
capture interval and the presence of navigation data
modulation on the GPS signal. If the signal weremodulated only by the C/A code and contained nonavigation data modulation, maximum theoreticallypossible acquisition sensitivity results from what weshall call “fully coherent” delay and Doppler
processing. In this form of processing the baseband
signal is frequency shifted and precessioncompensated in steps (Doppler bins), and for eachstep the signal is cross-correlated with a replica of
the C/A code spanning the entire signal observationinterval. Alternatively, the 1-msec periods of the C/Acode could be synchronously summed prior to crosscorrelation.
However, the presence of the 50 bps navigation
data modulation precludes the use of fully coherent
processing over the entire signal capture interval
unless some means is available to reliably strip themodulation from the signal. A common method of
dealing with the presence of data modulation is tocoherently process the signal within each data bitinterval, followed by noncoherent summation of theresults. The usual implementation of this technique
is to first coherently sum the 20 periods of thecomplex baseband C/A coded signal within eachdata bit. For each data bit a waveform is produced
which contains one 1-msec period of the C/A code,with a processing gain of 10log(20) = 13 dB. Eachwaveform is then cross-correlated with a replica of
the C/A code to produce a complex-valued crosscorrelation function. The squared magnitudes of thecross-correlation functions are computed andsummed to produce a single function spanning 1

millisecond, and the location of the peak value of thefunction is the signal delay estimate. We shall callthis form of processing “partially coherent.”
Figure 3 compares the performance of fully coherent
and partially coherent processing for a signal
observation time of 1 second. For fully coherent
processing there must be no data modulation on thesignal. Since data modulation always exists oncurrent C/A-coded GPS signals, fully coherent
processing cannot be used without knowledge of thedata bit polarities. However, its performance isused as a baseline reference to show how much islost when partially coherent processing is used. The
performance criterion used for both methods is theprobability of error in estimating the correct delay bin
by locating the peak of the cross-correlation function.
Examination of Figure 3 reveals that there is adifference in sensitivity between the two methods ofapproximately 3 dB at larger signal levels and about
4 dB as low signal levels, when 1 second of signal isobserved. It is important to note that fully coherent
processing has a major drawback—many more
delay/Doppler bins must be processed, which either
dramatically slows down processing speed or
requires a large amount of parallel processing tomaintain that speed.
This drawback can be ameliorated by using only
partially coherent processing with a longer signal
capture interval. Figure 4 shows the theoreticallyachievable performance of partially coherent
processing for signal capture intervals of 1, 2, and 4seconds. The processing gain increases by only
about 1.5 – 2 dB for each doubling of the captureinterval as compared to 3 dB for fully coherent
processing. However, it must be kept in mind thatwith fully coherent processing the number of Doppler
bins also doubles at each step, a property notpossessed with partially coherent processing. Thishas the effect of reducing the probability of detecting
the correct Doppler/delay bin.
An alternate method of achieving a delay estimate is
to detect the data bits and use them to homogenize
the polarity of the signal, this permitting coherent
processing over the full signal capture interval. In
order for this method to be effective, the signal must
be strong enough to ensure reliable data bit
detection.
Furthermore, a phase reference isneeded, and it should be estimated using the entire
signal observation.
A practical technique for
estimating phase, which approaches theoretically
optimum results, is the method of maximumlikelihood (ML). We shall call this methodology

“coherent processing with data stripping,” or simply“data stripping” for short.
Figure 5 shows how the performance using data
stripping compares with fully coherent and partiallycoherent processing. At low signal power levels(less than about –160 dBm) its performance
approaches that of partially coherent processing,and at high signal levels its performance approaches
that of fully coherent processing. At first glance, it
seems that data stripping might give a worthwhileadvantage over partially coherent processing.
However, it shares a common disadvantage withfully coherent processing in that a larger number ofdelay/Doppler bins must be processed, and the costis often prohibitive.
Receiver Bandwidth,
Ranging Accuracy

Sampling

Rate,

1
éB 2
ù
2
ê ò f S m ( f ) df ú
æ C ö ê -B
ú
8p 2 ç
÷ê B
ú
N
2
è 0ø
ê ò S m ( f ) df úëê - Bûú

(1)

where s e is the variance of the ranging error in2

seconds, C N 0 is the ratio of signal power to the
one-sided power spectral density of the noise,

S m ( f ) is the unfiltered power spectrum of the C/Acode, and 2B is the receiver RF bandwidth.
Because of the normalization by the denominatorintegral in (1), the power spectrum of the code canbe expressed using any convenient scaling. The
noise power spectral density is

N 0 = kt

The mathematical model for the normalized power
spectrum of the unfiltered C/A code isS m ( f ) = sinc ( f f c ) =sin (p f fc )(p f f c )(3)

where f c = 1.023 ´ 106, which is the C/A codechipping rate.
Although in reality the power
spectrum consists of spectral lines with 1 kHz
spacing, negligible error is incurred by using thismodel.

andA theoretical limit to pseudoranging accuracy,
imposed by the signal bandwidth and the ratio ofreceived signal power level to noise power spectral
density, is the Cramer-Rao (CR) bound, which isvalid for unbiased estimators. Fortuitously, thelocation of the peak of the cross-correlation of the
GPS signal with a C/A code replica is an unbiased
estimator of range (or at least the bias can becompensated), so calculation of the CR boundapplies. It can be shown that the CR bound for
ranging is given bys e2 ³where k = 1.38 ´ 10-23 is Boltzmann’s constant and t
is the noise temperature in degrees Kelvin, assumed
here to be 290o for an ideal receiver.

(2)

Figure 6 shows the CR bound computed from (1) asa function of received signal power using a C/A
coded signal, 1 second of signal observation time,and various values of RF bandwidth. For purposesof simplicity in using expression (1), it is assumed
that the receiver filters the code with an ideal brickwall filter. The curves in Figure 6 apply under theassumption that the correct delay bin has beenfound during signal acquisition. It has been verified
by simulations that if this is the case, the standard
deviation of range estimation error will actually meet
the bound (in other words, the bound is tight) for
signal power levels exceeding –157 dBm.
The curves of Figure 6 clearly show that range
errors due to thermal noise are much larger at thelow signal levels experienced indoors, as comparedto operation with clear line-of-sight (LOS) signals.
For example, a C/A code receiver operating with a –130 dBm signal (the minimum guaranteed level for
LOS reception at the Earth’s surface) will have anoise-induced range error standard deviation of
about 20-25 cm if its RF bandwidth is 16 MHz. On
the other hand, Figure 6 shows that the range error
standard deviation cannot be less than about 6
meters at -158 dBm, assuming the same
bandwidth—a substantial increase.
Therefore, it might appear even more important tohave a large RF bandwidth in a receiver designed
for weak-signal operation, especially consideringthat multipath performance will also be significantly
improved. However, this requires a proportionately
higher sampling rate for digitizing the signals. In a
conventional receiver this is usually not a serious
drawback, but in weak-signal receivers designed for
emergency operation the signal must be captured inmemory to permit rapid acquisition of the satellites,
and the higher sampling rate causes the memory
size to increase proportionally. Furthermore, thenumber of delay bins in the correlation process also
becomes proportionately larger, making it moredifficult and costly to rapidly process the signals.
Fortunately, the positioning accuracy requirements
for emergency operation are not unduly stringent (50meters RMS being typical). For this reason, theYokozuna system uses a relatively small RF
bandwidth of 1 MHz to keep the sampling rate low
and reduce the size of memory. At this bandwidth
the loss in SNR of the C/A coded signal isacceptably small (approximately –1 dB).
Determination of Accurate Time
In order to obtain accurate pseudoranges, aconventional GPS receiver obtains time informationfrom the navigation data message which permits theprecise GPS time of transmission of any part of thereceived signal to be tracked at the receiver. Whena group of pseudorange measurements is made, thetime of transmission from each satellite is used fortwo purposes: (1) To obtain an accurate position ofeach satellite at the time of transmission, and (2) tocompute pseudorange by computing the difference
between signal reception time (according to thereceiver clock) and transmission time.
In order to obtain time information from the received
GPS signal, a conventional receiver must go throughthe steps of acquiring the satellite signal, tracking itwith a phaselock loop to form a coherent reference
for data demodulation, achieve bit synchronization,
demodulate the data, achieve frame synchronization,
locate the portion of the navigation message whichcontains the time information, and finally, continue tokeep track of time (usually by counting C/A code
epochs as they are received).
However, it is desirable to avoid these numerous
and time-consuming steps in a positioning system
which must reliably obtain a position within several
seconds of startup in a weak-signal environment.
Because the navigation data message contains time
information only once per 6-second subframe, thereceiver may have to wait a minimum of 6 seconds
to obtain it (additionally, more time is needed tophase lock to the signal and achieve bit and frame
synchronization). Furthermore, data demodulation
becomes unreliable with weak signals (the bit error
rate rapidly becomes large at received signal power
levels below approximately -154 dBm).
In assisted GPS systems designed for rapid
positioning (within several seconds) using weaksignals, the client receiver does not have time toread unambiguous time from the received GPS

signal itself. If the approximate position of the client
is known with sufficient accuracy (perhaps within
100 km), it is possible to resolve the difference intimes of transmission. This is possible because thetimes of transmission of the C/A code epochs are
known to be integer multiples of 1 millisecond
according to SV time (which can be corrected to
GPS time using slowly-changing time correction data
sent from the server). This integer ambiguity indifferences of time transmission is resolved by using
approximate ranges to the satellites, which arecalculated from the approximate position of the clientand insertion of approximate time into satellite
ephemeris data sent by the server to the client. For
this purpose the accuracy of the approximated timeneeds to be sufficiently small to avoid excessive
uncertainty in the satellite positions. Generally atime accuracy of better than 10 seconds will suffice.
Once the ambiguity of the differences intransmission times has been resolved, accurate
positioning is possible if the positions of the satellites
at transmission time are known with an accuracy
comparable to the positioning accuracy desired.
However, since the satellites are moving at atangential orbital velocity of approximately 3800
meters/sec, the accuracy in knowledge of signaltransmission time for the purpose of locating thesatellites must be significantly more accurate thanthat required for the ambiguity resolution previously
described.
Most assisted GPS rapid-positioning systems using
weak signals obtain the necessary time accuracy forlocating the satellites by using time informationtransmitted from the server. It is important torecognize that such time information must be in“real-time,” that is, it must have a sufficiently small
uncertainty in latency as it arrives at the client
receiver. For example, a latency uncertainty of 0.1
second could result in a satellite position error of 380
meters along its orbital path, causing a positioning
error of the same order of magnitude.
Transmission of time from the server with smalllatency uncertainty has a major impact on the designof the server-to-client communication system, and isa major disadvantage in getting the providers ofexisting communication systems, such as cellular
networks, to become involved in providing indoor
assisted GPS positioning service.
The Yokozuna system has solved this problem witha major breakthrough using a synergistic
combination of two proprietary methods for obtaining
time information which does not require thecommunication system to transmit low-latency timingdata. Although the details of the technique are notpresented here, its performance is summarized in
the following table:
PDOP Range

RMS Error in Time Used for
Computing Satellite Position (msec)

PDOP < 55 £ PDOP < 1010 £ PDOP < 2020 £ PDOP < 40

2.7
5.2
10.5
22.1

From the table it is seen that for PDOP < 10 theRMS time error of 5.2 msec or less implies that the
RMS satellite position uncertainty along its orbital
path will not exceed (5.2 msec) ´ (3800 m/sec orbital
speed) =19.8 meters, with a concomitant
positioning error of comparable value.
Frequency Uncertainty
To achieve rapid positioning the range of frequency
uncertainty in acquiring the satellites at the client
receiver must be reduced as much as practicable inorder to reduce the search time. For this reason it iscommon practice in assisted GPS systems for theserver to transmit Doppler information to the client
receiver. However, if nothing more is done, thefrequency uncertainty of the receiver local oscillator
still remains as an obstacle to rapid acquisition.
Today’s technology can produce oscillators whichhave a frequency uncertainty on the order of ±1 partper million at a cost low enough to permit
incorporation into a consumer product such as a cell
phone. Even so, 1 part per million translates into
about ±1575 Hz of frequency uncertainty at the GPS
L1 frequency.
Assuming that the coherent
integration time during satellite search is 20
milliseconds (the length of a navigation message
data bit), the frequency bins in the search would
have a 50 Hz spacing, and a total of 2 ´ 1575/50 =63 frequency bins might have to be searched to findthe first satellite. Once the first satellite is acquired,
the local oscillator offset can be determined, and thefrequency uncertainty in searching for the remaining
satellites can thereby be reduced to very smallvalues. To remedy the problem of acquiring the firstsatellite in a sufficiently short time, some assisted
GPS systems use an accurate frequency reference
which is transmitted from the server to the client, in
addition to satellite Doppler measurements.
However, this requirement significantly complicatesthe design of the server-to-client communication
system, and is certainly undesirable when trying touse an existing communication system for assisting
purposes. If the communication system is a cell

phone network, every cell tower would need totransmit a precise frequency reference.
To avoid this problem in the Yokozuna system,some proprietary techniques have just been
completed to more quickly estimate the local
oscillator offset without the need for transmission ofa frequency reference to the client.
Fading and Multipath
It is well known that GPS signals received indoors
can be susceptible to fading and multipath which istypically more severe than when the receiver has aclear view of the sky.
FadingFading is the loss of signal strength caused bydestructive phase cancellation from signals that
arrive via two or more paths, and is usually
distinguished from absorptive loss when the signal
passes through objects such as the roof or walls of abuilding. The main defense against fading is simply
to use a high-sensitivity receiver, which not only iscapable of pulling a fading signal out of the noise,
but also might allow the reception of enoughsatellites to permit discarding the most severely
faded signals. Other defenses, such as diversity
reception, are not practical in the areas ofapplication intended for the Yokozuna system.
Preliminary tests of the system, to be described later,suggest that its sensitivity is high enough toeffectively combat fading in severe indoor
environments.
Multipath
Pseudorange errors due to multipath arise when the
cross correlation function generated by the receiver
is distorted by the presence of a GPS signal arriving
at the receiver antenna via two or more paths having
different propagation delays. GPS reception indoors
is particularly susceptible to multipath, because thedirect path signal can be greatly attenuated byabsorption while the secondary path components,
due to reflections, can be considerably larger.
However, because the the indoor positioning
accuracy requirements for the Yokozuna system areless stringent than for most standard receivers, themultipath error tends to be less detrimental.
Additionally, personnel working on the Yokozuna
project have considerable experience with inreceiver multipath mitigation technology, and arecapableofdeveloping
effective
mitigation
techniques if necessary.

IV. PRELIMINARY TEST RESULTS

Test #3: An Improved Positioning Algorithm

Preliminary field tests of the sensitivity andpositioning accuracy of the Yokozuna system,
performed with off-the-air satellite signals underdemanding conditions, are presented here.

Further development of the new positioning
algorithm has significantly improved positioning
accuracy. A comparison of the old and improved
algorithm is shown in Figure 9. The data for this test
was also obtained in Osaka, Japan in July 2004 at
the same test site used in Test #2. The testing
method was also the same, using a single rooftop
antenna for both server and client.
However,
several different values of attenuation were used forthe client: 2 cases with 0 dB, 5 cases with 20 dB,
and 5 cases with 30 dB. For each of the 12 cases
there are two positions shown in the figure, one
using the old positioning algorithm (red “X”) and one
using the improved version (green dot). It is readily
seen that the improved algorithm more than meetsthe goal of positioning within 50 meters RMS.

Test #1
This test was performed in Yokosuka, Japan in April
2004. The client receiver was located on the 4th
floor of a 7-story concrete and steel office building,with the receiver antenna on a chair under a steeltopped desk approximately 20 meters from an
outside wall of the building.
The server receiver, an Ashtech Model GG24 withspecial firmware for assisting purposes, and its
antenna were located on the building rooftop wherestrong line-of-sight satellite signals could bereceived. At the time of this test a server-to-client
radio link was not yet available, so the assisting datafrom the server was transmitted to the client via a
100 meter cable dropped through a stairwell fromthe roof to the 4th floor.
The results of this test are shown in Figure 7. The
blue map pin indicates the true position of the client
receiver, and the red map pins are the positions
obtained by the client receiver with assistance fromthe server. Most of the positions (about 80%)clustered within a radius of 60 meters from the true
position. There are some outliers, which most likely
were produced by high PDOP, marginal reception,
and/or multipath. After this test was performed, an
improved positioning algorithm was developed which
would have resulted in a significant reduction in thepositioning errors shown (see Test #3 below).
Test #2
This test was performed in Osaka, Japan in July
2004. An active GPS antenna was located on theroof of a 3-story concrete laboratory building. The
output from this antenna was split to provide signals
to both the server and Yokozuna client receivers.
However, the signal to the client receiver, located onndthe 2 floor, was attenuated by 40 dB to obtainweak-signal reception characteristic of an indoor
location.
The results of this test are shown in Figure 8. The
red map pins show positions obtained by the same
positioning algorithm that was used in Test #1, andthe yellow map pins show positions obtained by a
new positioning algorithm still under development.

Test #4: 200 km Server-Client Baseline
Figure 10 shows open sky positioning results
obtained on September 7, 2004, under extreme
weather conditions due to a typhoon in the area. In
this test the server was at the same location as in
Test #2 (Osaka, Japan), but the client receiver was
located at Lake Hamana, Japan, about 200 km
distant. A PHS (personal handy phone system)
network was used for communication of the assistingdata from server to client.
V. FURTHER DEVELOPMENTS
Work is continuing to improve Yokozuna system
performance. Currently a requirement for open sky
positioning error has been met by reducing this error
to 7-8 meters RMS or better. Further work, such as
integrity monitoring, should increase the overall
reliability of the system. Laboratory measurementsof client receiver sensitivity are also anticipated.
VI. SUMMARYThe Yokozuna system has shown great promise inachieving desired goals of high sensitivity,
positioning accuracy, and compatibility of use withexisting communication systems for assisting
purposes. The major advantage of this system isthat it can provide rapid and accurate positioning
using a variety of assisting systems without the needto modify these systems in order to provide timing
synchronization or accurate frequency calibration.
VII. FIGURES
Figures are shown on the following pages.

CLIENTSSERVERRF TUNER & A/D CONVERTERGPS REFERENCE
RECEIVERDOPPLER COMPENSATIONSTREAMING(BROADCAST)

INTERNET COMMUNICATION NETWORKPN POLARITY COMPENSATIONSERVER
DIGITAL SIGNAL
PROCESSING BLOCKASSISTED INFORMATION FOR SUPERSENSITIVITY.
Note: The system does not require any Time
Synchronization between Server and Clients

PSEUDORANGE MEASUREMENTCOMPUTATION OF POSITION

Magellan Systems Japan, Inc. Proprietary Information

Figure 1
The Yokozuna System
1575.42MHzCHIP ANTENNA

I

A/D

BPF

RF TUNERDOPPLERCOMPENSATION(Multi channel)

POLARITYCOMPENSATIONDIGITAL
PROCCESING
BLOCK

4.092MHz IFFREQUENCYSYNTHESIZER

Q

4.092MHz
16.368MHz XTALCOMMUNICATIONCARDCORRELATION
BLOCK
90

CPU

PEAK DETECTORSERVER INFORMATIONPOSITION COMPUTING BLOCK

Magellan Systems Japan, Inc. Proprietary Information

Figure 2
Yokozuna Client ReceiverEFFECT OF SIGNAL CAPTURE TIME INTERVALUSING PARTIALLY COHERENT PROCESSINGCOHERENT vs PARTIALLY COHERENT PROCESSING
0

0

R 10
O
R
R
E
N
I
B10 -1
Y
A
L
E
/D
R
E -2
L 10
P
P
O
D
F
O
Y -3
T
I 10
IL
B
A
B
O
R -4
P10

PARTIALLY COHERENT
50 COHERENTLY PROCESSED
20-MILLLISECOND INTERVALS
1-SEC FULLY COHERENTNONCOHERENTLY SUMMED

1023 DELAY BINS

1023 DELAY BINS

3200 DOPPLER BINS

64 DOPPLER BINSSIGNAL OBSERVATION TIME = 1 SEC
DOPPLER UNCERTAINTY = +/- 1600 HZ

-166

-164

-162

-160

-158

-156

-154

-152

-150

R10
O
R
R
E
IN
B -1
Y10
A
L
E
D
/
R
E
L -2
P10
P
O
D
F
O
Y -3
IT10
IL
B
A
B
O
R
P10 -4

N = 200(T = 4 SEC)

N COHERENTLY PROCESSED
20-MILLISECOND INTERVALSNONCOHERENTLY SUMMED
1023 DELAY BINS
64 DOPPLER BINS
DOPPLER UNCERTAINTY = +/- 1600 HZ

-164

-163

-161

-160

-159

-158

Figure 3

Figure 4

1-SEC PARTIALLY COHERENT

20-MILLISECOND INTERVALSNONCOHERENTLY SUMMED
1023 DELAY BINS

1023 DELAY BINS
3200 DOPPLER BINS

64 DOPPLER BINS

1-SEC FULLY COHERENT

1-SEC COHERENT(NO DATA MODULATION)

WITH DATA STRIPPING

-158

-157

-156

-155

-157

-156

-155

-154

CRAMER-RAO BOUND ON RANGE ERROR
) 100
(m
R
O
R
R
E
E
G
N
A
R
F
O
N 10
IO
T
IA
V
E
D
D
R
A
D
N
A
T
S

50 COHERENTLY PROCESSED

-159

-162

SIGNAL POWER (dBm)

COHERENT PROCESSING WITH DATA STRIPPING

-160

50
(1 SEC)SIGNAL POWER (dBm)

0

R 10
O
R
R
E
N
I
B -1
Y 10
A
L
E
D
/
R
E -2
L 10
P
P
O
D
F
O
Y 10-3
T
I
L
I
B
A
B
O
R -4
P 10

100
(2 SEC)-154

1

SIGNAL OBSERVATION TIME = 1 SECOND

2

C/A CODED SIGNAL

4
8
16
SIGNALBANDWIDTH (MHZ)

290 DEG KELVIN NOISE TEMPERATURE
C/No

1
-168

8

10

12

-166

-164

-162

14

16

18

20

22

24

-160

-158

-156

-154

-152

-150

SIGNAL POW ER (dBm)

SIGNAL POWER (dBm)

Figure 5

Figure 6-148

Figure 7. Positioning Results of Test #1

Figure 8. Positioning Results of Test #2

IMPROVEMENT OF POSITIONING ALGORITHM
100
POSITIONS FROM OLD ALGORITHM
MEAN = (0.1, -6.6) STD = (23.2, 42.4)
POSITIONS FROM NEW ALGORITHM
MEAN = (2.6, -4.0) STD = (7.6, 9.9)

50

)
M
(
R
O
R
R 0
E
H
T
R
O
N
-50

-100
-100

-50

0

50

100

EAST ERROR (M)

Figure 9

Figure 10. Positioning Results of Test #4