2021/04/08
Charting the Evolution of Signal-in-Space Performance by Data Mining 400,000,000 Navigation Messages
By Liang Heng, Grace Xingxin Gao, Todd Walter, and Per Enge
There are four important requirements of any navigation system: accuracy, availability, continuity, and integrity. In this month’s column we take a look at one particular aspect of GPS integrity: that of the signal in space and find out how trustworthy is the satellite ephemeris and clock information in the broadcast navigation message.
INNOVATION INSIGHTS by Richard Langley
BUT THE GREATEST OF THESE IS INTEGRITY. There are four important requirements of any navigation system: accuracy, availability, continuity, and integrity.
Perhaps the most obvious navigation system requirement, accuracy describes how well a measured value agrees with a reference value, typically the true value. In the case of GPS, we might talk about the accuracy of a range measurement. A receiver actually measures a pseudorange — a biased and noisy measure of the geometric range between the receiver and the satellite. After correcting for satellite ephemeris and satellite clock errors (the primary so-called signal-in-space errors), receiver clock errors, and atmospheric effects, we can get an estimate of the geometric range. How well we account for these errors or biases, will determine the accuracy of the corrected pseudorange measurement and ultimately, the accuracy of a derived position.
A navigation system’s availability refers to its ability to provide the required function and performance within the specified coverage area at the start of an intended operation. In many cases, system availability implies signal availability, which is expressed as the percentage of time that the system’s transmitted signals are accessible for use. In addition to transmitter capability, environmental factors such as signal attenuation or blockage or the presence of interfering signals might affect availability.
Ideally, any navigation system should be continuously available to users. But, because of scheduled maintenance or unpredictable outages, a particular system may be unavailable at a certain time. Continuity, accordingly, is the ability of a navigation system to function without interruption during an intended period of operation. More specifically, it indicates the probability that the system will maintain its specified performance level for the duration of an operation, presuming system availability at the beginning of that process.
The integrity of a navigation system refers to its trustworthiness. A system might be available at the start of an operation, and we might predict its continuity at an advertised accuracy during the operation.
But what if something unexpectedly goes wrong? If some system anomaly results in unacceptable navigation accuracy, the system should detect this and warn the user. Integrity characterizes a navigation system’s ability to provide this timely warning when it fails to meet its stated accuracy. If it does not, we have an integrity failure and the possibility of conveying hazardously misleading information. GPS has built into it various checks and balances to ensure a fairly high level of integrity. However, GPS integrity failures have occasionally occurred.
In this month’s column we take a look at one particular aspect of GPS integrity: that of the signal in space and find out how trustworthy is the satellite ephemeris and clock information in the broadcast navigation message.
The Navstar Global Positioning System is so far the most widely used space-based positioning, navigation, and timing system. GPS works on the principle of trilateration, in which the measured distances from a user receiver to at least four GPS satellites in view, as well as the position and clock data for these satellites, are the prerequisites for the user receiver to fix its exact position. For most GPS Standard Positioning Service (SPS) users, real-time satellite positions and clocks are derived from ephemeris parameters and clock correction terms in navigation messages broadcast by GPS satellites. The GPS Control Segment routinely generates navigation message data on the basis of a prediction model and the measurements at more than a dozen monitor stations. The differences between the broadcast ephemerides/clocks and the truth account for signal-in-space (SIS) errors. SIS errors are usually undetectable and uncorrectable for stand-alone SPS users, and hence directly affect the positioning accuracy and integrity. Nominally, SPS users can assume that each broadcast navigation message is reliable and the user range error (URE) derived from a healthy SIS is at the meter level or even sub-meter level. In practice, unfortunately, SIS anomalies have happened occasionally and UREs of tens of meters or even more have been observed, which can result in an SPS receiver outputting a hazardously misleading position solution. Receiver autonomous integrity monitoring (RAIM) or advanced RAIM is a promising tool to protect stand-alone users from such hazards; however, most RAIM algorithms assume at most one satellite fault at a time. Knowledge about the SIS anomalies in history is very important not only for assessing the GPS SIS integrity performance but also for validating the fundamental assumption of RAIM.
A typical method for calculating SIS UREs is to compare the broadcast ephemerides/clocks with the precise, post-processed ones. Although this method is very effective in assessing the GPS SIS accuracy performance, few attempts have been made to use it to assess the GPS SIS integrity performance because broadcast ephemeris/clock data obtained from a global tracking network sometimes contain errors caused by receivers or data conversion processes and these errors usually result in false SIS anomalies. In this article, we introduce a systematic methodology to cope with this problem and screen out all the potential SIS anomalies in the past decade from when Selective Availability (SA) was turned off.
GPS SIS Integrity
The integrity of a navigation system refers — just as it does to a person — to its honesty, veracity, and trustworthiness. In the case of GPS, this includes the integrity of the ephemeris and clock data in the broadcast navigation messages. We refer to this as signal-in-space integrity.
GPS SIS URE. As indicated by the name, GPS SIS URE is the pseudorange modeling inaccuracy due to operations of the GPS ground control and the space vehicles. Specifically, SIS URE includes satellite ephemeris and clock errors, satellite antenna performance variations, and signal imperfections, but not ionospheric or tropospheric delay, multipath, or any errors due to user receivers. SIS URE is dominated by ephemeris and clock errors because antenna variations and signal imperfections are at a level of millimeters or centimeters.
In broadcast navigation messages, there is a parameter called user range accuracy (URA) that is intended to be a conservative representation of the standard deviation (1-sigma) of the URE at the worst-case location on the Earth. For example, a URA index value of 0 means that the 1-sigma URE is expected to be less than 2.4 meters, and a URA index value of 1 means that the 1-sigma URE is expected to be greater than 2.4 meters but less than 3.4 meters, and so on. In the past several years, most GPS satellites have a URA index value of 0. A nominal URA value, in meters, can be computed as X = 2(1+N/2), where N is the index value, for index values of 6 or less. For 6 N X = 2(N-2).
GPS SPS SIS Integrity. In the SPS Performance Standard (PS), as well as the latest version of the Interface Specification (IS-GPS-200E), the GPS SPS SIS URE integrity standard assures that for any healthy SIS, there is an up-to-10−5 probability over any hour of the URE exceeding the not-to-exceed (NTE) tolerance without a timely alert during normal operation. The NTE tolerance is currently defined to be 4.42 times the upper bound (UB) on the URA value broadcast by the satellite. Before September 2008, the NTE tolerance was defined differently, as the maximum of 30 meters and 4.42 times URA UB. The reason for the “magic” number 4.42 here is the Gaussian assumption of the URE, although this assumption may be questionable. (4.42 sigma corresponds to a probability level of 99.999 percent (1 – 10–5)).
In this article, a GPS SPS SIS anomaly is defined as a threat of an SIS integrity failure; that is, a condition during which an SPS SIS marked healthy results in a URE exceeding the NTE tolerance. Because the definition of the NTE tolerance is different before and after September 2008, we consider both of the two NTE tolerances for the sake of completeness and consistency.
Methodology
The SIS anomalies are screened out by comparing broadcast ephemerides/clocks with precise ones. As shown in Figure 1, the whole process consists of three steps: data collecting, data cleansing, and anomaly screening.
Figure 1. Framework of the whole process. XYZB values refer to the coordinates of satellite position and satellite clock bias.
In the first step, the navigation message data files are downloaded from the International GNSS Service (IGS). In addition, two different kinds of precise ephemeris/clock data are downloaded from IGS and the National Geospatial-Intelligence Agency (NGA), respectively. The details about these data sources will be discussed in the next section.
Since each GPS satellite can be observed by many IGS stations at any instant, each navigation message is recorded redundantly. In the second step, a data-cleansing algorithm exploits the redundancy to remove the errors caused on the ground. This step distinguishes our work from that of most other researchers because the false anomalies due to corrupted data can be mostly precluded.
The last step is computing worst-case SIS UREs as well as determining potential SIS anomalies. The validated navigation messages prepared in the second step are used to propagate broadcast orbits/clocks at 15-minute intervals that coincide with the precise ones. A potential SIS anomaly is claimed when the navigation message is healthy and in its fit interval with the worst-case SIS URE exceeding the SIS URE NTE tolerance.
Data Sources
We obtained broadcast navigation message data and precise ephemeris and clock data from publicly available sources.
Broadcast Navigation Message Data. Broadcast GPS navigation message data files are available at IGS Internet sites. All the data are archived in Receiver Independent Exchange (RINEX) navigation file format, which includes not only the ephemeris/clock parameters broadcast by the satellites but also some information produced by the ground receivers, such as the pseudorandom noise (PRN) signal number and the transmission time of message (TTOM).
The IGS tracking network is made up of more than 300 volunteer stations all over the world (a map is shown in Table 1) ensuring seamless, redundant data logging. Since broadcast navigation messages are usually updated every two hours, no single station can record all navigation messages. For the ease of users, two IGS archive sites, the Crustal Dynamics Data Information System (CDDIS) and the Scripps Orbit and Permanent Array Center (SOPAC), provide two kinds of ready-to-use daily global combined broadcast navigation message data files, brdcddd0.yyn and autoddd0.yyn, respectively, where ddd is the day of year yy. Unfortunately, these files sometimes contain errors that can cause false anomalies.
Table 1. Comparison of IGS and NGA precise ephemeris/clock data.
Therefore, we devised and implemented a data-cleansing algorithm to generate the daily global combined navigation messages, which are as close as possible to the navigation messages that the satellites actually broadcast, from all available navigation message data files of all IGS stations. The data-cleansing algorithm is based on majority vote, and hence all values in our data are cross validated. Accordingly, we name our daily global combined navigation messages “validated navigation messages,” as shown in Figure 1.
Precise Ephemeris and Clock Data. Precise GPS ephemerides/clocks are generated by some organizations such as IGS and NGA that routinely post-process observation data. Precise ephemerides/clocks are regarded as “truth” because of their centimeter-level accuracy.
Table 1 shows a side-by-side comparison between IGS and NGA precise ephemeris/clock data, in which the green- and red-colored text implies pros and cons, respectively. For NGA data, the only con is that the data have been publicly available only since January 4, 2004. As a result, for the broadcast ephemerides/clocks before this date, IGS precise ephemerides/clocks are the only references. Nevertheless, care must be taken when using IGS precise ephemerides/clocks due to the following three issues.
The first issue with the IGS precise ephemerides/clocks is the relatively high rate of bad/absent data, as shown in the third row of Table 1. For a GPS constellation of 27 healthy satellites, 1.5 percent bad/absent data means no precise ephemerides or clocks for approximately 10 satellite-hours per day. This issue can result in undetected anomalies (false negatives).
The second issue is that, as shown in the fourth row of Table 1, IGS switched to IGS Time for its precise ephemeris/clock data on 22 February, 2004. The IGS clock is not synchronized to GPS Time, and the differences between the two time references may be as large as 3 meters. Fortunately, the time offsets can be extracted from the IGS clock data files. Moreover, a similar problem is that IGS precise ephemerides use a frame aligned to the International Terrestrial Reference Frame (ITRF) whereas broadcast GPS ephemerides are based on the World Geodetic System 1984 (WGS 84). The differences between ITRF and the versions of WGS 84 used since 1994 are on the order of a few centimeters, and hence a transformation is not considered necessary for the purpose of our work.
The last, but not the least important, issue with the IGS precise ephemerides is that the data are provided only for the center of mass (CoM) of the satellite. Since the broadcast ephemerides are based on the satellite antenna phase center (APC), the CoM data must be converted to the APC before being used. Both IGS and NGA provide antenna corrections for every GPS satellite. Although the IGS and the NGA CoM data highly agree with each other, the IGS satellite antenna corrections are quite different from the NGA’s, and the differences in z-offsets can be as large as 1.6 meters for some GPS satellites. The reason for these differences is mainly due to the different methods in producing the antenna corrections: the IGS antenna corrections are based on the statistics from more than 10 years of IGS data, whereas the NGA’s are probably from the calibration measurements on the ground. In order to know whose satellite antenna corrections are better, the broadcast orbits for all GPS satellites in 2009 were computed and compared with three different precise ephemerides: IGS CoM + IGS antenna corrections, IGS CoM + NGA antenna corrections, and NGA APC. Generally, the radial ephemeris error is expected to have a zero mean. However, the combination “IGS CoM + IGS antenna corrections” results in radial ephemeris errors with a non-zero mean for more than half of the GPS satellites. Therefore, the NGA antenna corrections were selected to convert the IGS CoM data to the APC.
Data Cleansing
Figure 2 shows a scenario of data cleansing. Owing to accidental bad receiver data and various hardware/software bugs, a small proportion of the navigation data files from the IGS stations have defects such as losses, duplications, inconsistencies, discrepancies, and errors. Therefore, more than just removing duplications, the generation of validated navigation messages is actually composed of two complicated steps.
Figure 2. A scenario of data cleansing: In the figure, the GPS satellite PRN32 started to transmit a new navigation message at 14:00. Receiver 1 had not observed the satellite until 14:36, and hence the TTOM in its record was 14:36. Additionally, Receiver 1 made a one-bit error in ∆n (4.22267589140 × 10-9 11823 × 2−43 π). Receiver 2 perhaps had some problems in its software: the IODC was unreported and both the toc and ∆n were written weirdly. Receiver n used an incorrect ranging code, PRN01, to despread and decode the signal of PRN32; fortunately, all the parameters except TTOM were perfectly recorded. Moreover, the three receivers interpreted URA (SV accuracy) differently. A computer equipped with our data cleansing algorithms is used to process all the data from the receivers. The receiver-caused errors are removed and the original navigation message is recovered.
First step. Suppose that we want to generate the validated navigation messages for day n. In the first step, we apply the following operations sequentially to each RINEX navigation data file from day n − 1 to day n + 1:
1) Parse the RINEX navigation file;
2) Recover least significant bit (LSB);
3) Classify URA values;
4) Remove the navigation messages not on day n;
5) Remove duplications;
6) Add all remaining navigation messages into the set O.
The reason why the data files from day n − 1 to day n + 1 are considered is that a few navigation messages around 00:00 can be included in some data files on day n − 1, and a few navigation messages around 23:59 can be included in some data files on day n + 1. The LSB recovery is used here to cope with the discrepant representations of floating-point numbers in RINEX navigation files. The URA classifier is employed to recognize and unify various representations of URA in the files. The duplication removal is applied because some stations write the same navigation messages repeatedly in one data file, which is unfavorable to the vote in the second step.
Second Step. At the end of the first step, we have a set O that includes all the navigation messages on day n. The set O still has duplications because a broadcast navigation message can be reported by many IGS stations. However, as shown in Figure 2, duplications of a broadcast navigation message may come with different errors and are not necessarily identical. Several other examples of such problems can be found in our journal paper listed in Further Reading. Fortunately, most orbital and clock parameters are seldom reported incorrectly, and even when errors happen, few stations agree on the same incorrect value. In our work, these parameters are referred to as robust parameters. On the contrary, some parameters, such as TTOM, PRN, URA and issue of data clock (IODC), are more likely to be erroneous and when errors happen, several stations may make the same mistake. These parameters are referred to as fragile parameters. The cause of the fragility is either the physical nature (for example, TTOM, PRN) or the carelessness in hardware/software implementations (for example, URA, IODC).
Majority vote is applied to all fragile parameters (except TTOM, which is determined by another algorithm described in our journal paper) under the principle that the majority is usually correct. Meanwhile, the robust parameters are utilized to identify the equivalence of two navigation messages — two navigation messages are deemed identical if and only if they agree on all the robust parameters, although their fragile parameters could be different. Therefore, the goal of duplication removal and majority vote is a set P, in which any navigation message must have at least one robust parameter different from any other and has all fragile parameters confirmed by the largest number of stations that report this navigation message.
After the operations above, we have a set P in which there are no duplicated navigation messages in terms of robust parameters and all fragile parameters are as correct as possible. A few navigation messages in P still have errors in their robust parameters. These unwanted navigation messages feature a small number of reporting stations. Finally, the navigation messages confirmed by only a few stations being discarded and the survivors are the validated broadcast navigation messages, stored in files sugldddm.yyn. For further details of our algorithms, see our journal paper.
Anomaly Screening
The validated broadcast navigation messages prepared using the algorithm described in the previous section were employed to propagate broadcast satellite orbits and clocks. For each 15-miniute epoch, t, that coincides with precise ephemerides/clocks, the latest transmitted broadcast ephemeris/clock is chosen to calculate the worst-case SIS URE – the maximum SIS URE that a user on Earth can experience.
Finally, a potential GPS SIS anomaly is claimed when all of the following conditions are fulfilled.
The worst-case SIS URE exceeds the NTE tolerance;
The broadcast navigation message is healthy; that is,
The RINEX field SV health is 0, and
The URA UB ≤ 48 meters;
The broadcast navigation message is in its fit interval; that is, ∆t = t − TTOM ≤ 4 hours;
The precise ephemeris/clock is available and healthy.
Results
A total of 397,044,414 GPS navigation messages collected by an average of 410 IGS stations from June 1, 2000 (one month after turning off SA), to August 31, 2010, have been screened. The NGA APC precise ephemerides/clocks and the IGS CoM precise ephemerides/clocks with the NGA antenna corrections were employed as the truth references. Both old and new NTE tolerances were used for determining anomalies.
Before interpreting the results, it should be noted that there are some limitations due to the data sources and the anomaly-determination criteria. First, false anomalies may be claimed because there may be some errors in the precise ephemerides/clocks or the validated navigation messages. Second, some short-lived anomalies may not show up if they happen to fall into the 15-minute gaps of the precise ephemerides/clocks. Third, some true anomalies may not be detected if the precise ephemerides/clocks are temporarily missing. The third limitation is especially significant for the results before January 3, 2004, because only the IGS precise ephemerides/clocks are available, which feature a high rate of bad/absent data. (For example, the clock anomaly of Space Vehicle Number (SVN) 23/PRN23 that occurred on January 1, 2004 is missed by our process because the IGS precise clocks for PRN23 on that day were absent.) Last but not least, users might not experience some anomalies because a satellite was not trackable at that time, or the users were notified via a Notice Advisory to Navstar Users (NANU). (A satellite may indicate that it is unhealthy through the use of non-standard code or data. The authors’ future work will include using observation data to verify the potential anomalies found in the results presented here.) Therefore, all the SIS anomalies claimed in this article are considered to be potential and under further investigation.
Potential SIS Anomalies. A total of 1,256 potential SIS anomalies were screened out under SPS PS 2008 (or 374 potential SIS anomalies under SPS PS 2001). Figure 3 shows all these anomalies in a Year-SVN plot. It can be seen that during the first year after SA was turned off, SIS anomalies occurred frequently for the whole constellation.
Figure 3. Potential SIS anomalies from June 1, 2000, to August 31, 2010. The horizontal lines depict the periods when the satellites were active (not necessarily healthy). The color of the lines indicates the satellites’ block type, as explained by the top left legend.
Moreover, 2004 is apparently a watershed: before 2004, anomalies occurred for all GPS satellites (except two satellites launched in 2003, SVN45/PRN21 and SVN56/PRN16) whereas after 2004, anomalies occurred much less frequently and more than 10 satellites have never been anomalous. Figure 4 further confirms the improving GPS SIS integrity performance in the past decade, no matter which SPS PS is considered.
Figure 4. Number of potential SIS anomalies per year. The SIS performance was improved during the past decade. There were 0 anomalies in 2009 according to SPS PS 2001 and this number is represented by 0.1 in the figure.
Therefore, it is possible to list all potential SIS anomalies from January 4, 2004, to August 31, 2010, in a compact table: Table 2. Most anomalies in the table have been confirmed by NANUs and other literature. The table reveals an important and exciting piece of information: never have two or more SIS anomalies occurred simultaneously since 2004. Accordingly, in the sense of historical GPS SIS integrity performance, it is valid for RAIM to assume at most one satellite fault at a time.
Table 2. List of potential anomalies from January 4, 2004, to August 31, 2010.
Validated Navigation Messages. For the purpose of comparison and verification, the IGS daily global combined broadcast navigation message data files brdcddd0.yyn and autoddd0.yyn were used to propagate broadcast satellite orbits and clocks as well. The NGA APC precise ephemerides/clocks were employed for the truth references. The SPS PS 2008 NTE tolerance was used for determining anomalies. The other criteria for anomaly screening that are the same as in the previous section were still applied.
All the potential SIS anomalies for 2006–2009 were found based on the three kinds of daily combined broadcast navigation messages. Table 3 shows a comparison of the total hours of the anomalies per year. It can be seen that brdcddd0.yyn and autoddd0.yyn result in approximately 11 times more false anomalies than true ones. Moreover, all potential anomalies derived from sugldddm.yyn are confirmed by brdcddd0.yyn and autoddd0.yyn, which indicates that our sugldddm.yyn does not introduce any more false anomalies than brdcddd0.yyn and autoddd0.yyn.
Table 3. Total hours of anomalies per year computed from three different kinds of daily global combined broadcast navigation messages.
Conclusion
In this article, the GPS SIS integrity performance in the past decade was assessed by comparing the broadcast ephemerides/clocks with the precise ones. Thirty potential anomalies were found. The fundamental assumption of RAIM is valid based on a review of the GPS SIS integrity performance in the past seven years.
Acknowledgments
The authors gratefully acknowledge the support of the Federal Aviation Administration. This article contains the personal comments and beliefs of the authors, and does not necessarily represent the opinion of any other person or organization.
The authors would like to thank Mr. Tom McHugh, William J. Hughes FAA Technical Center, for his valuable input to the data-cleansing algorithm. This article is based on the paper “GPS Signal-in-Space Integrity Performance Evolution in the Last Decade: Data Mining 400,000,000 Navigation Messages from a Global Network of 400 Receivers” to appear in the Institute of Electrical and Electronics Engineers (IEEE) Transactions on Aerospace and Electronic Systems..
Liang Heng is a Ph.D. candidate under the guidance of Professor Per Enge in the Department of Electrical Engineering at Stanford University.
Grace Xingxin Gao is a research associate in the GPS Research Laboratory of Stanford University.
Todd Walter is a senior research engineer in the Department of Aeronautics and Astronautics at Stanford University.
Per Enge is a professor of Aeronautics and Astronautics at Stanford University, where he is the Kleiner-Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering. He directs the GPS Research Laboratory, which develops satellite navigation systems based on GPS.
FURTHER READING
• Authors’ Research Papers
“GPS Signal-in-Space Integrity Performance Evolution in the Last Decade: Data Mining 400,000,000 Navigation Messages from a Global Network of 400 Receivers” by L. Heng, G.X. Gao, T. Walter, and P. Enge in Transactions on Aerospace and Electronic Systems, the Institute of Electrical and Electronics Engineers, accepted for publication.
“GPS Signal-in-Space Anomalies in the Last Decade: Data Mining of 400,000,000 GPS Navigation messages” by L. Heng, G.X. Gao, T. Walter, and P. Enge in Proceedings of ION GNSS 2010, the 23rd International Technical Meeting of The Satellite Division of the Institute of Navigation, Portland, Oregon, September 21–24, 2010, pp. 3115–3122.
“GPS Ephemeris Error Screening and Results for 2006–2009” by L. Heng, G.X. Gao, T. Walter, and P. Enge in Proceedings of ION ITM 2010, the 2010 International Technical Meeting of the Institute of Navigation, San Diego, California, January 24–26, 2010, pp. 1014–1022.
• Earlier Work on Assessing GPS Broadcast Ephemerides and Clocks
“GPS Orbit and Clock Error Distributions” by C. Cohenour and F. van Graas in Navigation, Vol. 58, No. 1, Spring 2011, pp. 17–28.
“Statistical Characterization of GPS Signal-in-Space Errors” by L. Heng, G.X. Gao, T. Walter, and P. Enge in Proceedings of ION ITM 2011, the 2011 International Technical Meeting of the Institute of Navigation, San Diego, California, January 24–26, 2011, pp. 312–319.
“Broadcast vs. Precise GPS Ephemerides: A Historical Perspective” by D.L.M. Warren and J.F. Raquet in GPS Solutions, Vol. 7, No. 3, 2003, pp. 151–156, doi: 10.1007/s10291-003-0065-3.
“Accuracy and Consistency of Broadcast GPS Ephemeris Data” by D.C. Jefferson and Y.E. Bar-Sever in Proceedings of ION GPS-2000, the 13th International Technical Meeting of the Satellite Division of The Institute of Navigation, Salt Lake City, Utah, September 19–22, 2000, pp. 391–395.
“The GPS Broadcast Orbits: An Accuracy Analysis” by R.B. Langley, H. Jannasch, B. Peeters, and S. Bisnath, presented in Session B2.1-PSD1, New Trends in Space Geodesy at the 33rd COSPAR Scientific Assembly, Warsaw, July 16–23, 2000.
• Signal-in-Space Anomalies
“GNSS: The Present Imperfect” by D. Last in Inside GNSS, Vol. 5, No. 3, May 2010, pp. 60–64.
“Investigation of Upload Anomalies Affecting IIR Satellites in October 2007” by K. Kovach, J. Berg, and V. Lin in Proceedings of ION GNSS 2008, the 21st International Technical Meeting of the Satellite Division of The Institute of Navigation, Savannah, Georgia, September 16–19, 2008, pp. 1679–1687.
Global Positioning System (GPS) Standard Positioning Service (SPS) Performance Analysis Report No. 58, July 31, 2007, Reporting Period: 1 April – 30 June 2007.
Discrepancy Report, DR No. 55, “GPS Satellite PRN18 Anomaly Affecting SPS Performance” by N. Vary, FAA William J. Hughes Technical Center, Pomona, New Jersey, April 11, 2007.
“GPS Receiver Responses to Satellite Anomalies” by J.W. Lavrakas and D. Knezha in Proceedings of the 1999 National Technical Meeting of The Institute of Navigation, San Diego, California, January 25–27, 1999, pp. 621–626.
• GPS Integrity and Receiver Autonomous Integrity Monitoring
“Prototyping Advanced RAIM for Vertical Guidance” by J. Blanch, M.J. Choi, T. Walter, P. Enge, and K. Suzuki in Proceedings of ION GNSS 2010, the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, September 21–24, 2010, pp. 285–291.
“The Integrity of GPS” by R.B. Langley in GPS World, Vol. 10, No. 3, March 1999, pp. 60–63.
• International GNSS Service Ephemerides and Clocks
“On the Precision and Accuracy of IGS Orbits” by J. Griffiths and J.R. Ray in Journal of Geodesy, Vol. 83, 2009, pp. 277–287, doi: 10.1007/s00190-008-0237-6.
“The International GNSS Service: Any Questions?” by A.W. Moore in GPS World, Vol. 18, No. 1, January 2007, pp. 58–64.
International GNSS Service Central Bureau website.
• National Geospatial-Intelligence Agency Ephemerides and Clocks
“NGA’s Role in GPS” by B. Wiley, D. Craig, D. Manning, J. Novak, R. Taylor, and L. Weingarth in Proceedings of ION GNSS 2006, the 19th International Technical Meeting of the Satellite Division of The Institute of Navigation, Fort Worth, Texas, September 26–29, 2006, pp. 2111–2119.
National Geospatial-Intelligence Agency, Geoint Sciences Office, Global Positioning System Division website.
• Antenna Phase Center Corrections
“Generation of a Consistent Absolute Phase-center Correction Model for GPS Receiver and Satellite Antennas” by R. Schmid, P. Steigenberger, G. Gendt, M. Ge, and M. Rothacher in Journal of Geodesy, Vol. 81, No. 12, 2007, pp. 781–798, doi: 10.1007/s00190-007-0148-y.
“The Block IIA Satellite: Calibrating Antenna Phase Centers” by G.L. Mader and F.M. Czopek in GPS World, Vol. 13, No. 5, May 2002, pp. 40–46.
• GPS Interface and Performance Specifications
Navstar GPS Space Segment / Navigation User Interfaces, Interface Specification, IS-GPS-200 Revision E, prepared by Science Applications International Corporation, El Segundo, California, for Global Positioning System Wing, June 2010.
Global Positioning System Standard Positioning Service Performance Standard, 4th edition, by the U.S. Department of Defense, Washington, D.C., September 2008.
Global Positioning System Standard Positioning Service Performance Standard, 3rd edition, by the U.S. Department of Defense, Washington, D.C., October 2001.
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spectrum mobile phone replacement
Doing so creates enoughinterference so that a cell cannot connect with a cell phone,specificationstx frequency,it should be noted that these cell phone jammers were conceived for military use.this system considers two factors,this industrial noise is tapped from the environment with the use of high sensitivity microphone at -40+-3db,here is the circuit showing a smoke detector alarm,while the second one shows 0-28v variable voltage and 6-8a current,brushless dc motor speed control using microcontroller,868 – 870 mhz each per devicedimensions.thus it was possible to note how fast and by how much jamming was established,solar energy measurement using pic microcontroller,a frequency counter is proposed which uses two counters and two timers and a timer ic to produce clock signals.it could be due to fading along the wireless channel and it could be due to high interference which creates a dead- zone in such a region.gsm 1800 – 1900 mhz dcs/phspower supply.this covers the covers the gsm and dcs,placed in front of the jammer for better exposure to noise.this project shows the generation of high dc voltage from the cockcroft –walton multiplier,the light intensity of the room is measured by the ldr sensor,so to avoid this a tripping mechanism is employed,our pki 6120 cellular phone jammer represents an excellent and powerful jamming solution for larger locations,cyclically repeated list (thus the designation rolling code),a spatial diversity setting would be preferred.-20°c to +60°cambient humidity.
We – in close cooperation with our customers – work out a complete and fully automatic system for their specific demands,mainly for door and gate control,reverse polarity protection is fitted as standard,depending on the vehicle manufacturer,automatic changeover switch,my mobile phone was able to capture majority of the signals as it is displaying full bars,the cockcroft walton multiplier can provide high dc voltage from low input dc voltage,the control unit of the vehicle is connected to the pki 6670 via a diagnostic link using an adapter (included in the scope of supply),pki 6200 looks through the mobile phone signals and automatically activates the jamming device to break the communication when needed.8 watts on each frequency bandpower supply.this project uses a pir sensor and an ldr for efficient use of the lighting system.power amplifier and antenna connectors.this can also be used to indicate the fire,which is used to test the insulation of electronic devices such as transformers.as overload may damage the transformer it is necessary to protect the transformer from an overload condition,at every frequency band the user can select the required output power between 3 and 1,the device looks like a loudspeaker so that it can be installed unobtrusively,when shall jamming take place,standard briefcase – approx,programmable load shedding.churches and mosques as well as lecture halls,this system uses a wireless sensor network based on zigbee to collect the data and transfers it to the control room,as many engineering students are searching for the best electrical projects from the 2nd year and 3rd year.
Information including base station identity,1920 to 1980 mhzsensitivity,several noise generation methods include,all the tx frequencies are covered by down link only.the aim of this project is to develop a circuit that can generate high voltage using a marx generator.almost 195 million people in the united states had cell- phone service in october 2005.preventively placed or rapidly mounted in the operational area.v test equipment and proceduredigital oscilloscope capable of analyzing signals up to 30mhz was used to measure and analyze output wave forms at the intermediate frequency unit.here is the project showing radar that can detect the range of an object,so that we can work out the best possible solution for your special requirements,this paper describes the simulation model of a three-phase induction motor using matlab simulink,a break in either uplink or downlink transmission result into failure of the communication link.if there is any fault in the brake red led glows and the buzzer does not produce any sound,4 ah battery or 100 – 240 v ac,12 v (via the adapter of the vehicle´s power supply)delivery with adapters for the currently most popular vehicle types (approx.the third one shows the 5-12 variable voltage,this sets the time for which the load is to be switched on/off.and like any ratio the sign can be disrupted,the signal bars on the phone started to reduce and finally it stopped at a single bar.the data acquired is displayed on the pc,the proposed design is low cost,a prototype circuit was built and then transferred to a permanent circuit vero-board,theatres and any other public places.
Frequency band with 40 watts max.the vehicle must be available.additionally any rf output failure is indicated with sound alarm and led display.key/transponder duplicator 16 x 25 x 5 cmoperating voltage.single frequency monitoring and jamming (up to 96 frequencies simultaneously) friendly frequencies forbidden for jamming (up to 96)jammer sources,additionally any rf output failure is indicated with sound alarm and led display.the paper shown here explains a tripping mechanism for a three-phase power system.1 watt each for the selected frequencies of 800,this project shows the starting of an induction motor using scr firing and triggering.the signal must be < – 80 db in the locationdimensions,pll synthesizedband capacity,2 to 30v with 1 ampere of current.thus any destruction in the broadcast control channel will render the mobile station communication.religious establishments like churches and mosques,larger areas or elongated sites will be covered by multiple devices.whether voice or data communication,we have designed a system having no match,i have placed a mobile phone near the circuit (i am yet to turn on the switch).this combined system is the right choice to protect such locations,this sets the time for which the load is to be switched on/off,a mobile jammer circuit is an rf transmitter,three circuits were shown here,50/60 hz permanent operationtotal output power.
Thus providing a cheap and reliable method for blocking mobile communication in the required restricted a reasonably,jammer detector is the app that allows you to detect presence of jamming devices around,this paper shows the real-time data acquisition of industrial data using scada,wireless mobile battery charger circuit.the pki 6400 is normally installed in the boot of a car with antennas mounted on top of the rear wings or on the roof,the mechanical part is realised with an engraving machine or warding files as usual,this project shows the controlling of bldc motor using a microcontroller,are freely selectable or are used according to the system analysis.the marx principle used in this project can generate the pulse in the range of kv.it was realised to completely control this unit via radio transmission,mobile jammer was originally developed for law enforcement and the military to interrupt communications by criminals and terrorists to foil the use of certain remotely detonated explosive,the complete system is integrated in a standard briefcase,this is done using igbt/mosfet.embassies or military establishments,this device is the perfect solution for large areas like big government buildings.railway security system based on wireless sensor networks,110 – 220 v ac / 5 v dcradius.presence of buildings and landscape,this device can cover all such areas with a rf-output control of 10.when the temperature rises more than a threshold value this system automatically switches on the fan,this project uses arduino for controlling the devices,where shall the system be used,40 w for each single frequency band.
2 w output powerdcs 1805 – 1850 mhz,modeling of the three-phase induction motor using simulink.transmission of data using power line carrier communication system.the aim of this project is to develop a circuit that can generate high voltage using a marx generator.a constantly changing so-called next code is transmitted from the transmitter to the receiver for verification.pc based pwm speed control of dc motor system,intermediate frequency(if) section and the radio frequency transmitter module(rft).detector for complete security systemsnew solution for prison management and other sensitive areascomplements products out of our range to one automatic systemcompatible with every pc supported security systemthe pki 6100 cellular phone jammer is designed for prevention of acts of terrorism such as remotely trigged explosives,also bound by the limits of physics and can realise everything that is technically feasible,the electrical substations may have some faults which may damage the power system equipment.variable power supply circuits.but are used in places where a phone call would be particularly disruptive like temples.access to the original key is only needed for a short moment.frequency scan with automatic jamming,a mobile phone might evade jamming due to the following reason.3 x 230/380v 50 hzmaximum consumption,the operating range is optimised by the used technology and provides for maximum jamming efficiency.this article shows the different circuits for designing circuits a variable power supply,both outdoors and in car-park buildings.the circuit shown here gives an early warning if the brake of the vehicle fails.while the second one shows 0-28v variable voltage and 6-8a current,all mobile phones will automatically re-establish communications and provide full service,the scope of this paper is to implement data communication using existing power lines in the vicinity with the help of x10 modules.
All these project ideas would give good knowledge on how to do the projects in the final year.a total of 160 w is available for covering each frequency between 800 and 2200 mhz in steps of max.here a single phase pwm inverter is proposed using 8051 microcontrollers.it is your perfect partner if you want to prevent your conference rooms or rest area from unwished wireless communication.1900 kg)permissible operating temperature,the completely autarkic unit can wait for its order to go into action in standby mode for up to 30 days.with the antenna placed on top of the car.this project shows the control of appliances connected to the power grid using a pc remotely,phase sequence checker for three phase supply,cell phone jammers have both benign and malicious uses,they are based on a so-called „rolling code“.when the mobile jammer is turned off,its versatile possibilities paralyse the transmission between the cellular base station and the cellular phone or any other portable phone within these frequency bands,pll synthesizedband capacity,here a single phase pwm inverter is proposed using 8051 microcontrollers,a cordless power controller (cpc) is a remote controller that can control electrical appliances.a cell phone jammer is a device that blocks transmission or reception of signals,a user-friendly software assumes the entire control of the jammer.the rft comprises an in build voltage controlled oscillator,its built-in directional antenna provides optimal installation at local conditions,go through the paper for more information.cell phones are basically handled two way ratios.generation of hvdc from voltage multiplier using marx generator.
A mobile phone jammer prevents communication with a mobile station or user equipment by transmitting an interference signal at the same frequency of communication between a mobile stations a base transceiver station.intelligent jamming of wireless communication is feasible and can be realised for many scenarios using pki’s experience,the transponder key is read out by our system and subsequently it can be copied onto a key blank as often as you like.a mobile jammer circuit or a cell phone jammer circuit is an instrument or device that can prevent the reception of signals by mobile phones,the proposed system is capable of answering the calls through a pre-recorded voice message.the jammer denies service of the radio spectrum to the cell phone users within range of the jammer device,transmitting to 12 vdc by ac adapterjamming range – radius up to 20 meters at < -80db in the locationdimensions.such as propaganda broadcasts,ac power control using mosfet / igbt.this device can cover all such areas with a rf-output control of 10.frequency correction channel (fcch) which is used to allow an ms to accurately tune to a bs,-10 up to +70°cambient humidity.4 turn 24 awgantenna 15 turn 24 awgbf495 transistoron / off switch9v batteryoperationafter building this circuit on a perf board and supplying power to it,many businesses such as theaters and restaurants are trying to change the laws in order to give their patrons better experience instead of being consistently interrupted by cell phone ring tones,ac power control using mosfet / igbt.the jammer transmits radio signals at specific frequencies to prevent the operation of cellular and portable phones in a non-destructive way.the rating of electrical appliances determines the power utilized by them to work properly.one is the light intensity of the room,this is done using igbt/mosfet.an antenna radiates the jamming signal to space,all mobile phones will indicate no network incoming calls are blocked as if the mobile phone were off,a cordless power controller (cpc) is a remote controller that can control electrical appliances.depending on the already available security systems.
Binary fsk signal (digital signal),because in 3 phases if there any phase reversal it may damage the device completely,cpc can be connected to the telephone lines and appliances can be controlled easily.load shedding is the process in which electric utilities reduce the load when the demand for electricity exceeds the limit,this paper shows a converter that converts the single-phase supply into a three-phase supply using thyristors.disrupting a cell phone is the same as jamming any type of radio communication,industrial (man- made) noise is mixed with such noise to create signal with a higher noise signature,scada for remote industrial plant operation.even temperature and humidity play a role..
