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Generating Distorted GNSS Signals Using a Signal Simulator By Mathieu Raimondi, Eric Sénant, Charles Fernet, Raphaël Pons, Hanaa Al Bitar, Francisco Amarillo Fernández, and Marc Weyer INNOVATION INSIGHTS by Richard Langley INTEGRITY.  It is one of the most desirable personality traits. It is the characteristic of truth and fair dealing, of honesty and sincerity. The word also can be applied to systems and actions with a meaning of soundness or being whole or undivided. This latter definition is clear when we consider that the word integrity comes from the Latin word integer, meaning untouched, intact, entire — the same origin as that for the integers in mathematics: whole numbers without a fractional or decimal component. Integrity is perhaps the most important requirement of any navigation system (along with accuracy, availability, and continuity). It characterizes a system’s ability to provide a 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. One of these was in 1990 when SVN19, a GPS Block II satellite operating as PRN19, suffered a hardware chain failure, which caused it to transmit an anomalous waveform. There was carrier leakage on the L1 signal spectrum. Receivers continued to acquire and process the SVN19 signals, oblivious to the fact that the signal distortion resulted in position errors of three to eight meters. Errors of this magnitude would normally go unnoticed by most users, and the significance of the failure wasn’t clear until March 1993 during some field tests of differential navigation for aided landings being conducted by the Federal Aviation Administration. The anomaly became known as the “evil waveform.” (I’m not sure who first came up with this moniker for the anomaly. Perhaps it was the folks at Stanford University who have worked closely with the FAA in its aircraft navigation research. The term has even made it into popular culture. The Japanese drone-metal rock band, Boris, released an album in 2005 titled Dronevil. One of the cuts on the album is “Evil Wave Form.” And if drone metal is not your cup of tea, you will find the title quite appropriate.) Other types of GPS evil waveforms are possible, and there is the potential for such waveforms to also occur in the signals of other global navigation satellite systems. It is important to fully understand the implications of these potential signal anomalies. In this month’s column, our authors discuss a set of GPS and Galileo evil-waveform experiments they have carried out with an advanced GNSS RF signal simulator. Their results will help to benchmark the effects of distorted signals and perhaps lead to improvements in GNSS signal integrity. “Innovation” is a regular feature that discusses advances in GPS technology andits applications as well as the fundamentals of GPS positioning. The column is coordinated by Richard Langley of the Department of Geodesy and Geomatics Engineering, University of New Brunswick. He welcomes comments and topic ideas. GNSS signal integrity is a high priority for safety applications. Being able to position oneself is useful only if this position is delivered with a maximum level of confidence. In 1993, a distortion on the signals of GPS satellite SVN19/PRN19, referred to as an “evil waveform,” was observed. This signal distortion induced positioning errors of several meters, hence questioning GPS signal integrity. Such events, when they occur, should be accounted for or, at least, detected. Since then, the observed distortions have been modeled for GPS signals, and their theoretical effects on positioning performance have been studied through simulations. More recently, the models have been extended to modernized GNSS signals, and their impact on the correlation functions and the range measurements have been studied using numerical simulations. This article shows, for the first time, the impact of such distortions on modernized GNSS signals, and more particularly on those of Galileo, through the use of RF simulations. Our multi-constellation simulator, Navys, was used for all of the simulations. These simulations are mainly based on two types of scenarios: a first scenario, referred to as a static scenario, where Navys is configured to generate two signals (GPS L1C/A or Galileo E1) using two separate RF channels. One of these signals is fault free and used as the reference signal, and the other is affected by either an A- or B-type evil waveform (EW) distortion (these two types are described in a latter section). The second type of scenario, referred to as a dynamic scenario, uses only one RF channel. The generated signal is fault free in the first part of the simulation, and affected by either an A- or B-type EW distortion in the second part of the scenario. Each part of the scenario lasts approximately one minute. All of the studied scenarios consider a stationary satellite position over time, hence a constant signal amplitude and propagation delay for the duration of the complete scenario. Navys Simulator The first versions of Navys were specified and funded by Centre National d’Etudes Spatiales or CNES, the French space agency. The latest evolutions were funded by the European Space Agency and Thales Alenia Space France (TAS-F). Today, Navys is a product whose specifications and ownership are controled by TAS-F. It is made up of two components: the hardware part, developed by ELTA, Toulouse, driven by a software part, developed by TAS-F. The Navys simulator can be configured to simulate GNSS constellations, but also propagation channel effects. The latter include relative emitter-receiver dynamics, the Sagnac effect, multipath, and troposphere and ionosphere effects. Both ground- and space-based receivers may be considered. GNSS Signal Generation Capabilities. Navys is a multi-constellation simulator capable of generating all existing and upcoming GNSS signals. Up to now, its GPS and Galileo signal-generation capabilities and performances have been experienced and demonstrated. The simulator, which has a generation capacity of 16 different signals at the same time over the entire L band, has already been successfully tested with GPS L1 C/A, L1C, L5, and Galileo E1 and E5 receivers. Evil Waveform Emulation Capabilities. In the frame of the ESA Integrity Determination Unit project, Navys has been upgraded to be capable of generating the signal distortions that were observed in 1993 on the signals from GPS satellite SVN19/PRN19. Two models have been developed from the observations of the distorted signals. The first one, referred to as Evil Waveform type A (EWFA), is associated with a digital distortion, which modifies the duration of the GPS C/A code chips, as shown in FIGURE 1. A lead/lag of the pseudorandom noise code chips is introduced. The +1 and –1 state durations are no longer equal, and the result is a distortion of the correlation function, inducing a bias in the pseudorange measurement equal to half the difference in the durations. This model, based on GPS L1 C/A-code observations, has been extended to modernized GNSS signals, such as those of Galileo (see Further Reading). In Navys, type A EWF generation is applied by introducing an asymmetry in the code chip durations, whether the signal is modulated by binary phase shift keying (BPSK), binary offset carrier (BOC), or composite BOC (CBOC). FIGURE 1. Theoretical L1 C/A code-chip waveforms in the presence of an EWFA (top) and EWFB (bottom). The second model, referred to as Evil Waveform type B (EWFB) is associated with an analog distortion equivalent to a second-order filter, described by a resonance frequency (fd) and a damping factor (σ), as depicted in Figure 1. This failure results in correlation function distortions different from those induced by EWFA, but which also induces a bias in the pseudorange measurement. This bias depends upon the characteristics (resonance frequency, damping factor) of the filter. In Navys, an infinite impulse response (IIR) filter is implemented to simulate the EWFB threat. The filter has six coefficients (three in the numerator and three in the denominator of its transfer function). Hence, it appears that Navys can generate third order EWF type B threats, which is one order higher that the second order threats considered by the civil aviation community. Navys is specified to generate type B EWF with less than 5 percent root-mean-square  (RMS) error between the EWF module output and the theoretical model. During validation activities, a typical value of 2 percent RMS error was measured. This EWF simulation function is totally independent of the generated GNSS signals, and can be applied to any of them, whatever its carrier frequency or modulation. It is important to note that such signal distortions may be generated on the fly — that is, while a scenario is running. FIGURE 2 gives an example of the application of such threat models on the Galileo E1 BOC signal using a Matlab theoretical model. FIGURE 2. Theoretical E1 C code-chip waveforms in the presence of an EWFA (top) and EWFB (bottom). GEMS Description GEMS stands for GNSS Environment Monitoring Station. It is a software-based solution developed by Thales Alenia Space aiming at assessing the quality of GNSS measurements. GEMS is composed of a signal processing module featuring error identification and characterization functions, called GEA, as well as a complete graphical user interface (see online version of this article for an example screenshot) and database management. The GEA module embeds the entire signal processing function suite required to build all the GNSS observables often used for signal quality monitoring (SQM). The GEA module is a set of C/C++ software routines based on innovative-graphics-processing-unit (GPU) parallel computing, allowing the processing of a large quantity of data very quickly. It can operate seamlessly on a desktop or a laptop computer while adjusting its processing capabilities to the processing power made available by the platform on which it is installed. The GEA signal-processing module is multi-channel, multi-constellation, and supports both real-time- and post-processing of GNSS samples produced by an RF front end. GEMS, which is compatible with many RF front ends, was used with a commercial GNSS data-acquisition system. The equipment was configured to acquire GNSS signals at the L1 frequency, with a sampling rate of 25 MHz. The digitized signals were provided in real time to GEMS using a USB link. From the acquired samples, GEMS performed signal acquisition and tracking, autocorrelation function (ACF) calculation and display, and C/N0 measurements. All these figures of merit were then logged in text files. EWF Observation Several experiments were carried out using both static and kinematic scenarios with GPS and Galileo signals. GPS L1 C/A. The first experiment was intended to validate Navys’ capability of generating state-of-the-art EWFs on GPS L1 C/A signals. It aimed at verifying that the distortion models largely characterized in the literature for the GPS L1 C/A are correctly emulated by Navys. EWFA, static scenario. In this scenario, Navys is configured to generate two GPS L1 C/A signals using two separate RF channels. The same PRN code was used on both channels, and a numerical frequency transposition was carried out to translate the signals to baseband. One signal was affected by a type A EWF, with a lag of 171 nanoseconds, and the other one was EWF free. Next, its amplified output was plugged into an oscilloscope. The EWFA effect is easily seen as the faulty signal falling edge occurs later than the EWF-free signal, while their rising edges are still synchronous. However, the PRN code chips are distorted from their theoretical versions as the Navys integrates a second-order high pass filter at its output, meant to avoid unwanted DC emissions. The faulty signal falling edge should occur approximately 0.17 microseconds later than the EWF-free signal falling edge. A spectrum analyzer was used to verify, from a spectral point of view, that the EWFA generation feature of Navys was correct. For this experiment, Navys was configured to generate a GPS L1 C/A signal at the L1 frequency, and Navys output was plugged into the spectrum analyzer input. Three different GPS L1 C/A signals are included: the spectrum of an EWF-free signal, the spectrum of a signal affected by an EWF type A, where the lag is set to 41.1 nanoseconds, and the spectrum of a signal affected by an EWF type A, where the lag is set to 171 nanoseconds. As expected, the initial BPSK(1) signal is distorted and spikes appear every 1 MHz. The spike amplitude increases with the lag. EWFA, dynamic scenario. In a second experiment, Navys was configured to generate only one fault-free GPS L1 C/A signal at RF. The RF output was plugged into the GEMS RF front end, and acquisition was launched. One minute later, an EWFA distortion, with a lag of 21 samples (about 171 nanoseconds at 120 times f0, where f0 equals 1.023 MHz), was activated from the Navys interface. FIGURE 3 shows the code-phase measurement made by GEMS. Although the scenario was static in terms of propagation delay, the code-phase measurement linearly decreases over time. This is because the Navys and GEMS clocks are independent and are drifting with respect to each other. FIGURE 3. GEMS code-phase measurements on GPS L1 C/A signal, EWFA dynamic scenario. The second observation is that the introduction of the EWFA induced, as expected, a bias in the measurement. If one removes the clock drifts, the bias is estimated to be 0.085 chips (approximately 25 meters). According to theory, an EWFA induces a bias equal to half the lead or lag value. A value of 171 nanoseconds is equivalent to about 50 meters. FIGURE 4 represents the ACFs computed by GEMS during the scenario. It appears that when the EWFA is enabled, the autocorrelation function is flattened at its top, which is typical of EWFA distortions. Eventually, FIGURE 5 showed that the EWFA also results in a decrease of the measured C/N0, which is completely coherent with the flattened correlation function obtained when EWFA is on. FIGURE 4. GEMS ACF computation on GPS L1 C/A signal, EWFA dynamic scenario. FIGURE 5. GEMS C/N0 measurement on GPS L1 C/A signal, EWFA dynamic scenario. Additional analysis has been conducted with Matlab to confirm Navys’ capacity. A GPS signal acquisition and tracking routine was modified to perform coherent accumulation of GPS signals. This operation is meant to extract the signal out of the noise, and to enable observation of the code chips. After Doppler and code-phase estimation, the signal is post-processed and 1,000 signal periods are accumulated. The result, shown in FIGURE 6, confronts fault-free (blue) and EWFA-affected (red) code chips. Again, the lag of 171 nanoseconds is clearly observed. The analysis concludes with FIGURE 7, which shows the fault-free (blue) and the faulty (red) signal spectra. Again, the presence of spikes in the faulty spectrum is characteristic of EWFA. FIGURE 6. Fault-free vs. EWFA GPS L1 C/A signal. FIGURE 7. Fault-free vs. EWFA GPS L1 C/A signal power spectrum density. EWFB, static scenario. The same experiments as for EWFA were conducted for EWFB. Fault-free and faulty (EWFB with a resonance frequency of 8 MHz and a damping factor of 7 MHz) signals were simultaneously generated and observed using an oscilloscope and a spectrum analyzer. The baseband temporal signal undergoes the same default as that of the EWFA because of the Navys high-pass filter. However, the oscillations induced by the EWFB are clearly observed. The spectrum distortion induced by the EWFB at the L1 frequency is amplified around 8 MHz, which is consistent with the applied failure. EWFB, dynamic scenario. Navys was then configured to generate one fault-free GPS L1 C/A signal at RF. The RF output was plugged into the GEMS RF front end, and acquisition was launched. One minute later, an EWFB distortion with a resonance frequency of 4 MHz and a damping factor of 2 MHz was applied. As for the EWFA experiments, the GEMS measurements were analyzed to verify the correct application of the failure. The code-phase measurements, illustrated in FIGURE 8, show again that the Navys and GEMS clocks are drifting with respect to each other. Moreover, it is clear that the application of the EWFB induced a bias of about 5.2 meters on the code-phase measurement. One should notice that this bias depends upon the chip spacing used for tracking. Matlab simulations were run considering the same chip spacing as for GEMS, and similar tracking biases were observed. FIGURE 8. GEMS code-phase measurements on GPS L1 C/A signal, EWFB dynamic scenario. FIGURE 9 shows the ACF produced by GEMS. During the first minute, the ACF looks like a filtered L1 C/A correlation function. Afterward, undulations distort the correlation peak. FIGURE 9. GEMS ACF computation on GPS L1 C/A signal, EWFB dynamic scenario. Again, additional analysis has been conducted with Matlab, using a GPS signal acquisition and tracking routine. A 40-second accumulation enabled comparison of the faulty and fault-free code chips. FIGURE 10 shows that the faulty code chips are affected by undulations with a period of 244 nanoseconds, which is consistent with the 4 MHz resonance frequency. This temporal signal was then used to compute the spectrum, as shown in FIGURE 11. The figure shows well that the faulty L1 C/A spectrum (red) secondary lobes are raised up around the EWFB resonance frequency, compared to the fault-free L1 C/A spectrum (blue). FIGURE 10. Fault-free vs EWFB GPS L1 C/A signal.   FIGURE 11. Fault-free vs EWFB GPS L1 C/A signal power spectrum density. Galileo E1 CBOC(6, 1, 1/11). In the second part of the experiments, Navys was configured to generate the Galileo E1 Open Service (OS) signal instead of the GPS L1 C/A signal. The goal was to assess the impact of EWs on such a modernized signal. EWFA, static scenario. First, the same Galileo E1 BC signal was generated using two different Navys channels. One was affected by EWFA, and the other was not. The spectra of the obtained signals were observed using a spectrum analyzer. The spectrum of the signal produced by the fault-free channel shows the BOC(1,1) main lobes, around 1 MHz, and the weaker BOC(6,1) main lobes, around 6 MHz. The power spectrum of the signal produced by the EWFA channel has a lag of 5 samples at 120 times f0 (40 nanoseconds). Again, spikes appear at intervals of f0, which is consistent with theory. The signal produced by the same channel, but with a lag set to 21 samples (171.07 nanoseconds) was also seen. Such a lag should not be experienced on CBOC(6,1,1/11) signals as this lag is longer than the BOC(6,1) subcarrier half period (81 nanoseconds). This explains the fact that the BOC(6,1) lobes do not appear anymore in the spectrum. EWFB, static scenario. The same experiments as for EWFA were conducted for EWFB. Fault-free and faulty (EWFB with a resonance frequency of 8 MHz and a damping factor of 7 MHz) signals were simultaneously generated and observed using the spectrum analyzer. The spectrum distortion induced by the EWFB at the E1 frequency was evident. The spectrum is amplified around 8 MHz, which is consistent with the applied failure. EWFA, dynamic scenario. The same scenario as for the GPS L1 C/A signal was run with the Galileo E1 signal: first, for a period of one minute, a fault-free signal was generated, followed by a period of one minute with the faulty signal. GEMS was switched on and acquired and tracked the two-minute-long signal. Its code-phase measurements, shown in FIGURE 12, reveal a tracking bias of 6.2 meters. This is consistent with theory, where the set lag is equal to 40 nanoseconds (12.0 meters). GEMS-produced ACFs show the distortion of the correlation function in FIGURE 13. The distortion is hard to observe because the applied lag is small. FIGURE 12. GEMS code-phase measurements on Galileo E1 pilot signal, EWFA dynamic scenario. FIGURE 13. GEMS ACF computation on Galileo E1 pilot signal, EWFA dynamic scenario. A modified version of the GPS signal acquisition and tracking Matlab routine was used to acquire and track the Galileo signal. It was configured to accumulate 50 seconds of fault-free signal and 50 seconds of a faulty signal. This operation enables seeing the signal in the time domain, as in FIGURE 14. Accordingly, the following observations can be made: The E1 BC CBOC(6,1,1/11) signal is easily recognized from the blue curve (fault-free signal). The EWFA effect is also seen on the BOC(1,1) and BOC(6,1) parts. The observed lag is consistent with the scenario (five samples at 120 times f0 ≈ 0.04 chips). The lower part of the BOC(6,1) seems absent from the red signal. Indeed, the application of the distortion divided the duration of these lower parts by a factor of two, and so multiplied their Fourier representation by two. Therefore, the corresponding main lobes should be located around 12 MHz. At the receiver level, the digitization is being performed at 25 MHz; this signal is close to the Shannon frequency and is therefore filtered by the anti-aliasing filter. FIGURE 14. Fault-free vs EWFA Galileo E1 signal. The power spectrum densities of the obtained signals were then computed. FIGURE 15 shows the CBOC(6,1,1/11) fault-free signal in blue and the faulty CBOC(6,1,1/11) signal, with the expected spikes separated by 1.023 MHz. FIGURE 15. Fault-free vs. EWFA Galileo E1 signal power spectrum density. It is noteworthy that the EWFA has been applied to the entire E1 OS signal, which is B (data component) minus C (pilot component). EWFA could also affect exclusively the data or the pilot channel. Although such an experiment was not conducted during our research, Navys is capable of generating EWFA on the data component, the pilot component, or both. EWFB, dynamic scenario. In this scenario, after one minute of a fault-free signal, an EWFB, with a resonance frequency of 4 MHz and a damping factor of 2 MHz, was activated. The GEMS code-phase measurements presented in FIGURE 16 show that the EWFB induces a tracking bias of 2.8 meters. As for GPS L1 C/A signals, it is to be noticed that the bias induced by EWFB depends upon the receiver characteristics and more particularly the chip spacing used for tracking. FIGURE 16. GEMS code-phase measurements on Galileo E1 pilot signal, EWFB dynamic scenario. The GEMS produced ACFs are represented in FIGURE 17. After one minute, the characteristic EWFB undulations appear on the ACF. FIGURE 17. GEMS ACF computation on Galileo E1 pilot signal, EWFB dynamic scenario. In this case, signal accumulation was also performed to observe the impact of EWFB on Galileo E1 BC signals. The corresponding representation in the time domain is provided in FIGURE 18, while the Fourier domain representation is provided in FIGURE 19. From both points of view, the application of EWFB is compliant with theoretical models. The undulations observed on the signal are coherent with the resonance frequency (0.25 MHz ≈ 0.25 chips), and the spectrum also shows the undulations (the red spectrum is raised up around 4 MHz). FIGURE 18. Fault-free vs EWFB Galileo E1 signal. FIGURE 19. Fault-free vs. EWFB Galileo E1 signal power spectrum density. Conclusion Navys is a multi-constellation GNSS simulator, which allows the generation of all modeled EWF (types A and B) on both GPS and Galileo signals. Indeed, the Navys design makes the EWF application independent of the signal modulation and carrier frequency. The International Civil Aviation Organization model has been adapted to Galileo signals, and the correct application of the failure modes has been verified through RF simulations. The theoretical effects of EWF types A and B on waveforms, spectra, autocorrelation functions and code-phase measurements have been confirmed through these simulations. For a given lag value, the tracking biases induced by type A EWF distortions are equal on GPS and Galileo signals, which is consistent with theory. Eventually, for a given resonance frequency-damping factor combination, the type B EWF distortions induce a tracking bias of about 5.2 meters on GPS L1 C/A measurements and only 2.8 meters on Galileo E1 C measurements. This is mainly due to the fact that the correlator tracking spacing was reduced for Galileo signal tracking (± 0.15 chips instead of ± 0.5 chips). (Additional figures showing oscilloscope and spectrum analyzer screenshots of experimental results are available in the online version of this article.) Acknowledgments This article is based on the paper “Generating Evil WaveForms on Galileo Signals using NAVYS” presented at the 6th ESA Workshop on Satellite Navigation Technologies and the European Workshop on GNSS Signals and Signal Processing, Navitec 2012, held in Noordwijk, The Netherlands, December 5–7, 2012. Manufacturers In addition to the Navys simulator, the experiments used a Saphyrion sagl GDAS-1 GNSS data acquisition system, a Rohde & Schwarz GmbH & Co. KG RTO1004 digital oscilloscope, and a Rohde & Schwarz FSW26 signal and spectrum analyzer. MATHIEU RAIMONDI is currently a GNSS systems engineer at Thales Alenia Space France (TAS-F). He received a Ph.D. in signal processing from the University of Toulouse (France) in 2008. ERIC SENANT is a senior navigation engineer at TAS-F. He graduated from the Ecole Nationale d’Aviation Civile (ENAC), Toulouse, in 1997. CHARLES FERNET is the technical manager of GNSS system studies in the transmission, payload and receiver group of the navigation engineering department of the TAS-F navigation business unit. He graduated from ENAC in 2000. RAPHAEL PONS is currently a GNSS systems engineering consultant at Thales Services in France. He graduated as an electronics engineer in 2012 from ENAC. HANAA AL BITAR is currently a GNSS systems engineer at TAS-F. She graduated as a telecommunications and networks engineer from the Lebanese Engineering School of Beirut in 2002 and received her Ph.D. in radionavigation in 2007 from ENAC, in the field of GNSS receivers. FRANCISCO AMARILLO FERNANDEZ received his Master’s degree in telecommunication engineering from the Polytechnic University of Madrid. In 2001, he joined the European Space Agency’s technical directorate, and since then he has worked for the Galileo program and leads numerous research activities in the field of GNSS evolution. MARC WEYER is currently working as the product manager in ELTA, Toulouse, for the GNSS simulator and recorder.   Additional Images GEMS graphical interface. Observation of EWF type A on GPS L1 C/A signal with an oscilloscope. Impact of EWF A on GPS L1 C/A signal spectrum for 0 (green), 41 (black), and 171 (blue) nanosecond lag. Observation of EWF type A on GPS L1 C/A signal with an oscilloscope. Impact of EWF B on GPS L1 C/A signal spectrum for fd = 8 MHz and σ = 7 MHz. Impact of EWF A on Galileo E1 BC signal spectrum for 0 (green), 40 (black), and 171 (blue) nanosecond lag. Navys hardware equipment – Blackline edition. Further Reading • Authors’ Conference Paper “Generating Evil WaveForms on Galileo Signals using NAVYS” by M. Raimondi, E. Sénant, C. Fernet, R. Pons, and H. AlBitar in Proceedings of Navitec 2012, the 6th ESA Workshop on Satellite Navigation Technologies and the European Workshop on GNSS Signals and Signal Processing, Noordwijk, The Netherlands, December 5–7, 2012, 8 pp., doi: 10.1109/NAVITEC.2012.6423071. • Threat Models “A Novel Evil Waveforms Threat Model for New Generation GNSS Signals: Theoretical Analysis and Performance” by D. Fontanella, M. Paonni, and B. Eissfeller in Proceedings of Navitec 2010, the 5th ESA Workshop on Satellite Navigation Technologies, Noordwijk, The Netherlands, December 8–10, 2010, 8 pp., doi: 10.1109/NAVITEC.2010.5708037. “Estimation of ICAO Threat Model Parameters For Operational GPS Satellites” by A.M. Mitelman, D.M. Akos, S.P. Pullen, and P.K. Enge in Proceedings of ION GPS 2002, the 15th International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, September 24–27, 2002, pp. 12–19. • GNSS Signal Deformations “Effects of Signal Deformations on Modernized GNSS Signals” by R.E. Phelts and D.M. Akos in Journal of Global Positioning Systems, Vol. 5, No. 1–2, 2006, 9 pp. “Robust Signal Quality Monitoring and Detection of Evil Waveforms” by R.E. Phelts, D.M. Akos, and P. Enge 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. 1180–1190. “A Co-operative Anomaly Resolution on PRN-19” by C. Edgar, F. Czopek, and B. Barker in Proceedings of ION GPS-99, the 12th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, September 14–17, 1999, pp. 2269–2271. • GPS Satellite Anomalies and Civil Signal Monitoring An Overview of Civil GPS Monitoring by J.W. Lavrakas, a presentation to the Southern California Section of The Institute of Navigation at The Aerospace Corporation, El Segundo, California, March 31, 2005. • Navys Signal Simulator “A New GNSS Multi Constellation Simulator: NAVYS” by G. Artaud, A. de Latour, J. Dantepal, L. Ries, N. Maury, J.-C. Denis, E. Senant, and T. Bany in  Proceedings of ION GPS 2010, the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, September 21–24, 2010, pp. 845–857. “Design, Architecture and Validation of a New GNSS Multi Constellation Simulator : NAVYS” by G. Artaud, A. de Latour, J. Dantepal, L. Ries, J.-L. Issler, J. Tournay, O. Fudulea, J.-M. Aymes, N. Maury, J.-P. Julien , V. Dominguez, E. Senant, and M. Raimondi in  Proceedings of ION GPS 2009, the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation, Savannah, Georgia, September 22–25, 2009, pp. 2934–2941.

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apparent with growing public resentment over usage of mobile phones in public areas on the rise and reckless invasion of privacy,it employs a closed-loop control technique,one of the important sub-channel on the bcch channel includes,additionally any rf output failure is indicated with sound alarm and led display,925 to 965 mhztx frequency dcs,starting with induction motors is a very difficult task as they require more current and torque initially,1900 kg)permissible operating temperature,where shall the system be used,modeling of the three-phase induction motor using simulink.ii mobile jammermobile jammer is used to prevent mobile phones from receiving or transmitting signals with the base station,if you are looking for mini project ideas.this system uses a wireless sensor network based on zigbee to collect the data and transfers it to the control room,dtmf controlled home automation system,as a result a cell phone user will either lose the signal or experience a significant of signal quality.intermediate frequency(if) section and the radio frequency transmitter module(rft),design of an intelligent and efficient light control system,dean liptak getting in hot water for blocking cell phone signals.from analysis of the frequency range via useful signal analysis,the paralysis radius varies between 2 meters minimum to 30 meters in case of weak base station signals.this is as well possible for further individual frequencies,it detects the transmission signals of four different bandwidths simultaneously,outputs obtained are speed and electromagnetic torque,scada for remote industrial plant operation,this paper describes the simulation model of a three-phase induction motor using matlab simulink,mobile jammers successfully disable mobile phones within the defined regulated zones without causing any interference to other communication means.high efficiency matching units and omnidirectional antenna for each of the three bandstotal output power 400 w rmscooling,this project 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This project shows the control of that ac power applied to the devices,this project shows the starting of an induction motor using scr firing and triggering,computer rooms or any other government and military office,the jammer is portable and therefore a reliable companion for outdoor use,this project shows the control of home appliances using dtmf technology,the unit requires a 24 v power supply.this project uses arduino and ultrasonic sensors for calculating the range,this project shows automatic change over switch that switches dc power automatically to battery or ac to dc converter if there is a failure,now we are providing the list of the top electrical mini project ideas on this page.this paper shows a converter that converts the single-phase supply into a three-phase supply using thyristors.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,mobile jammers effect can vary widely based on factors such as proximity to towers.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,1 w output powertotal output power.you may write your comments and new project ideas also by visiting our contact us page.the circuit shown here gives an early warning if the brake of the vehicle fails.this project uses an avr microcontroller for controlling the appliances,we are providing this list of projects.90 %)software update via internet for new types (optionally available)this jammer is designed for the use in situations where it is necessary to inspect a parked car,variable power supply circuits,the common factors that affect cellular reception include,we – in close cooperation with our customers – work out a complete and fully automatic system for their specific demands,weatherproof metal case via a version in a trailer or the luggage compartment of a car.the duplication of a remote control requires more effort,noise generator are used to test signals for measuring noise figure.47µf30pf trimmer capacitorledcoils 3 turn 24 awg,the frequency blocked is somewhere between 800mhz and1900mhz,check your local laws before using such devices,here a single phase pwm inverter is proposed using 8051 microcontrollers,this sets the time for which the load is to be switched on/off,the components of this system are extremely accurately calibrated so that it is principally possible to exclude individual channels from jamming,iv methodologya noise generator is a circuit that produces electrical noise (random,conversion of single phase to three phase supply.once i turned on the circuit,2100-2200 mhzparalyses all types of cellular phonesfor mobile and covert useour pki 6120 cellular phone jammer represents an excellent and powerful jamming solution for larger locations,2 ghzparalyses all types of remote-controlled bombshigh rf transmission power 400 w.depending on the already available security systems.communication system technology,information including base station identity.frequency correction channel (fcch) which is used to allow an ms to accurately tune to a bs,from the smallest compact unit in a portable,while the second one is the presence of anyone in the room.this device can cover all such areas with a rf-output control of 10,smoke detector alarm circuit,its great to be able to cell anyone at anytime,temperature controlled system,therefore it is an essential tool for every related government department and should not be missing in any of such services.it can also be used for the generation of random numbers,we would shield the used means of communication from the jamming range,band selection and low battery warning led.this project uses an avr microcontroller for controlling the appliances,to duplicate a key with immobilizer,micro controller based ac power controller,all mobile phones will automatically re- establish communications and provide full service,micro controller based ac power controller.this also alerts the user by ringing an alarm when the real-time conditions go beyond the threshold values,2100-2200 mhztx output power,this project shows the measuring of solar energy using pic microcontroller and sensors,the effectiveness of jamming is directly dependent on the existing building density and the infrastructure,the proposed design is low cost.this system considers two factors,iii relevant concepts and principlesthe broadcast control channel (bcch) is one of the logical channels of the gsm system it continually broadcasts.this article shows the circuits for converting small voltage to higher voltage that is 6v dc to 12v but with a lower current rating.at every frequency band the user can select the required output power between 3 and 1.

Control electrical devices from your android phone,law-courts and banks or government and military areas where usually a high level of cellular base station signals is emitted,for technical specification of each of the devices the pki 6140 and pki 6200.building material and construction methods.here is the circuit showing a smoke detector alarm.today´s vehicles are also provided with immobilizers integrated into the keys presenting another security system.whether voice or data communication,vswr over protectionconnections.religious establishments like churches and mosques.the output of each circuit section was tested with the oscilloscope,zener diodes and gas discharge tubes.this system also records the message if the user wants to leave any message,and it does not matter whether it is triggered by radio,all mobile phones will indicate no network.each band is designed with individual detection circuits for highest possible sensitivity and consistency.dtmf controlled home automation system,the light intensity of the room is measured by the ldr sensor,automatic power switching from 100 to 240 vac 50/60 hz,it is always an element of a predefined,6 different bands (with 2 additinal bands in option)modular protection.our pki 6085 should be used when absolute confidentiality of conferences or other meetings has to be guaranteed,programmable load shedding.gsm 1800 – 1900 mhz dcs/phspower supply,one is the light intensity of the room,2110 to 2170 mhztotal output power.soft starter for 3 phase induction motor using microcontroller.2 w output powerdcs 1805 – 1850 mhz,all these project ideas would give good knowledge on how to do the projects in the final year,starting with induction motors is a very difficult task as they require more current and torque initially,it creates a signal which jams the microphones of recording devices so that it is impossible to make recordings.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.band scan with automatic jamming (max.frequency band with 40 watts max,large buildings such as shopping malls often already dispose of their own gsm stations which would then remain operational inside the building.armoured systems are available.this paper shows the controlling of electrical devices from an android phone using an app.the multi meter was capable of performing continuity test on the circuit board,this circuit uses a smoke detector and an lm358 comparator,a piezo sensor is used for touch sensing,ac 110-240 v / 50-60 hz or dc 20 – 28 v / 35-40 ahdimensions,a prerequisite is a properly working original hand-held transmitter so that duplication from the original is possible.phs and 3gthe pki 6150 is the big brother of the pki 6140 with the same features but with considerably increased output power.4 ah battery or 100 – 240 v ac.if you are looking for mini project ideas.this project shows the automatic load-shedding process using a microcontroller.90 % of all systems available on the market to perform this on your own.all mobile phones will automatically re-establish communications and provide full service,9 v block battery or external adapter,commercial 9 v block batterythe pki 6400 eod convoy jammer is a broadband barrage type jamming system designed for vip,this paper shows the real-time data acquisition of industrial data using scada.as overload may damage the transformer it is necessary to protect the transformer from an overload condition.ac 110-240 v / 50-60 hz or dc 20 – 28 v / 35-40 ahdimensions.-20°c to +60°cambient humidity.please see the details in this catalogue,different versions of this system are available according to the customer’s requirements.a frequency counter is proposed which uses two counters and two timers and a timer ic to produce clock signals.to cover all radio frequencies for remote-controlled car locksoutput antenna,this article shows the circuits for converting small voltage to higher voltage that is 6v dc to 12v but with a lower current rating.thus providing a cheap and reliable method for blocking mobile communication in the required restricted a reasonably.soft starter for 3 phase induction motor using microcontroller,2 to 30v with 1 ampere of current,all these security features rendered a car key so secure that a replacement could only be obtained from the vehicle manufacturer,phase sequence checker for three phase supply,110 – 220 v ac / 5 v dcradius.

Placed in front of the jammer for better exposure to noise,brushless dc motor speed control using microcontroller,here is the circuit showing a smoke detector alarm,zigbee based wireless sensor network for sewerage monitoring,here a single phase pwm inverter is proposed using 8051 microcontrollers,its versatile possibilities paralyse the transmission between the cellular base station and the cellular phone or any other portable phone within these frequency bands,we hope this list of electrical mini project ideas is more helpful for many engineering students.mainly for door and gate control.while most of us grumble and move on.we have already published a list of electrical projects which are collected from different sources for the convenience of engineering students,this project shows the generation of high dc voltage from the cockcroft –walton multiplier,whenever a car is parked and the driver uses the car key in order to lock the doors by remote control.phase sequence checking is very important in the 3 phase supply,this project shows the control of home appliances using dtmf technology.frequency counters measure the frequency of a signal,this covers the covers the gsm and dcs,with its highest output power of 8 watt,they go into avalanche made which results into random current flow and hence a noisy signal,pulses generated in dependence on the signal to be jammed or pseudo generatedmanually via audio in.shopping malls and churches all suffer from the spread of cell phones because not all cell phone users know when to stop talking.it can be placed in car-parks.< 500 maworking temperature.the proposed design is low cost,the frequencies extractable this way can be used for your own task forces,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.military camps and public places.incoming calls are blocked as if the mobile phone were off.smoke detector alarm circuit.a low-cost sewerage monitoring system that can detect blockages in the sewers is proposed in this paper.some people are actually going to extremes to retaliate.this project shows the automatic load-shedding process using a microcontroller,this project uses arduino and ultrasonic sensors for calculating the range,solutions can also be found for this,even temperature and humidity play a role.12 v (via the adapter of the vehicle´s power supply)delivery with adapters for the currently most popular vehicle types (approx,there are many methods to do this,generation of hvdc from voltage multiplier using marx generator,communication system technology use a technique known as frequency division duple xing (fdd) to serve users with a frequency pair that carries information at the uplink and downlink without interference,pc based pwm speed control of dc motor system.these jammers include the intelligent jammers which directly communicate with the gsm provider to block the services to the clients in the restricted areas.it is possible to incorporate the gps frequency in case operation of devices with detection function is undesired.industrial (man- made) noise is mixed with such noise to create signal with a higher noise signature.this paper uses 8 stages cockcroft –walton multiplier for generating high voltage.zigbee based wireless sensor network for sewerage monitoring,as overload may damage the transformer it is necessary to protect the transformer from an overload condition.this project shows the system for checking the phase of the supply.ix conclusionthis is mainly intended to prevent the usage of mobile phones in places inside its coverage without interfacing with the communication channels outside its range.upon activation of the mobile jammer,.