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A New Way to Test GNSS Receivers By Alexander Mitelman INNOVATION INSIGHTS by Richard Langley GNSS RECEIVER TESTING SHOULD NEVER BE LEFT TO CHANCE. Or should it? There are two common approaches to testing GNSS receivers: synthetic and realistic. In synthetic testing, a signal simulator is programmed with specific satellite orbits, receiver positions, and signal propagation conditions such as atmospheric effects, signal blockage, and multipath. A disadvantage of such testing is that the models used to generate the synthetic signals are not always consistent with the behavior of receivers processing real GNSS signals. Realistic testing, on the other hand, endeavors to assess receiver performance directly using the signals actually transmitted by satellites. The signals may be recorded digitally and played back to receivers any number of times. While no modeling is used, the testing is specific to the particular observing scenario under which the data was recorded including the satellite geometry, atmospheric conditions, multipath behavior, and so on. To fully examine the performance of a receiver using data collected under a wide variety of scenarios would likely be prohibitive. So, neither testing approach is ideal. Is there a practical alternative? The roulette tables in Monte Carlo suggest an answer. Both of the commonly used testing procedures lack a certain characteristic that would better assess receiver performance: randomness. What is needed is an approach that would easily provide a random selection of realistic observing conditions. Scientists and engineers often use repeated random samples when studying systems with a large number of inputs especially when those inputs have a high degree of uncertainty or variability. And mathematicians use such methods to obtain solutions when it is impossible or difficult to calculate an exact result as in the integration of some complicated functions. The approach is called the Monte Carlo method after the principality’s famous casino. Although the method had been used earlier, its name was introduced by physicists studying random neutron diffusion in fissile material at the Los Alamos National Laboratory during the Second World War. In this month’s article, we look at an approach to GNSS receiver testing that uses realistic randomization of signal amplitudes based on histograms of carrier-to-noise-density ratios observed in real-world environments. It can be applied to any simulator scenario, independent of scenario details (position, date, time, motion trajectory, and so on), making it possible to control relevant parameters such as the number of satellites in view and the resulting dilution of precision independent of signal-strength distribution. The method is amenable to standardization and could help the industry to improve the testing methodology for positioning devices — to one that is more meaningfully related to real-world performance and user experience. Virtually all GNSS receiver testing can be classified into one of two broad categories: synthetic or realistic. The former typically involves simulator-based trials, using a pre-defined collection of satellite orbits, receiver positions, and signal propagation models (ionosphere, multipath, and so on). Examples of this type of testing include the 3rd Generation Partnership Project (3GPP) mobile phone performance specifications for assisted GPS, as well as the “apples-to-apples” methodology described in an earlier GPS World article (see Further Reading). The primary advantage of synthetic testing is that it is tightly controllable and completely repeatable; where a high degree of statistical confidence is required, the same scenario can be run many times until sufficient data has been collected. Also, this type of testing is inherently self-contained, and thus amenable to testing facilities with modest equipment and resources. Synthetic approaches have significant limitations, however, particularly when it comes to predicting receiver performance in challenging real-world environments. Experience shows that tests in which signal levels are fixed at predetermined levels are not always predictive of actual receiver behavior. For example, a receiver’s coherent integration time could in principle be tuned to optimize acquisition at those levels, resulting in a device that passes the required tests but whose performance may degrade in other cases. More generally, it is useful to observe that the real world is full of randomness, whereas apart from intentional variations in receiver initialization, the primary source of randomness in most synthetic tests is simply thermal noise. By comparison, most realistic testing approaches are designed to measure real-world performance directly. Examples include conventional drive testing and so-called “RF playback” systems, both of which have also been described in recent literature (see Further Reading). Here, no modeling or approximation is involved; the receiver or recording instrument is physically operated within the signal environment of interest, and its performance in that environment is observed directly. The accuracy and fidelity of such tests come with a price, however. All measurements of this type are inherently literal: the results of a given test are inseparably linked to the specific multipath profile, satellite geometry, atmospheric conditions, and antenna profile under which the raw data was gathered. In this respect, the direct approach resembles the synthetic methods outlined above — little randomness exists within the test setup to fully explore a given receiver’s performance space. Designing a practical alternative to the existing GNSS tests, particularly one intended to be easy to standardize, represents a challenging balancing act. If a proposed test is too simple, it can be easily standardized, but it may fall well short of capturing the complexities of real-world signals. On the other hand, a test laden with many special corner cases, or one that requires users to deploy significant additional data storage or non-standard hardware, may yield realistic results for a wide variety of signal conditions, but it may also be impractically difficult to standardize. With those constraints in mind, this article attempts to bridge the gap between the two approaches described above. It describes a novel method for generating synthetic scenarios in which the distribution of signal levels closely approximates that observed in real-world data sets, but with an element of randomness that can be leveraged to significantly expand testing coverage through Monte Carlo methods. Also, the test setup requires only modest data storage and is easily implemented on existing, widely deployed hardware, making it attractive as a potential candidate for standardization. The approach consists of several steps. First, signal data is gathered in an environment of interest and used to generate a histogram of carrier-to-noise-density (C/N0) ratios as reported by a reference receiver, paying particular attention to satellite masking to ensure that the probability of signal blockage is calculated accurately. The histogram is then combined with a randomized timing model to create a synthetic scenario for a conventional GNSS simulator, whose output is fed into the receiver(s) under test (RUTs). The performance of the RUTs in response to live and simulated signals is compared in order to validate the fidelity and usefulness of the histogram-based simulation. This hybrid approach combines the benefits of synthetic testing (repeatability, full control, and compactness) with those of live testing (realistic, non-static distribution of signal levels), while avoiding many of the drawbacks of each. Histograms The method explored in this article relies on cumulative histograms of C/N0 values reported by a receiver in a homogeneous signal environment. This representation is compact and easy to implement with existing simulator-based test setups, and provides information that can be particularly useful in tuning acquisition algorithms. Motivation and Theoretical Considerations. To motivate the proposed approach, consider an example histogram constructed from real-world data, gathered in an environment (urban canyon) where A-GPS would typically be required. This is shown in FIGURE 1, together with a representative histogram of a standard “coarse-time assistance” test case (as described in the 3GPP Technical Standard 34.171, Section 5.2.1) for comparison. (Note that the x-axis is actually discontinuous toward the left side of each plot: the “B” column designates blocked signals, and thus corresponds to C/N0 = –∞.) From the standpoint of signal distributions, it is evident that existing test standards may not always model the real world very accurately. FIGURE 1a. Example histogram of a real-world urban canyon, the San Francisco financial district;. Figure 1b. Example histograms of 3GPP TS 34.171 “coarse-time assistance” test case). The histogram is useful in other ways as well. Since the data set is normalized (the sum of all bin heights is 1.0), it represents a proper probability mass function (PMF) of signal levels for the environment in question. As such, several potentially useful parameters can be extracted directly from the plot: the probability of a given signal being blocked (simply the height of the leftmost bin); upper and lower limits of observed signal levels (the heights of the leftmost and rightmost non-zero bins, respectively, excluding the “blocked” bin); and the center of mass, defined here as (1) where y[n] is the height of the nth bin (dimensionless), x[n] is the corresponding C/N0 value (in dB-Hz), and x[“B”] = –∞ by definition. Finally, representing environmental data as a PMF enables one additional theoretical calculation. The design of the 3GPP “coarse-time assistance” test case illustrated above assumes that a receiver will be able to acquire the one relatively strong signal (the so-called “lead space vehicle (SV)” at -142 dBm) using only the assistance provided, and will subsequently use information derivable from the acquired signal (such as the approximate local clock offset) to find the rest of the satellites and compute a fix. Suppose that for a given receiver, the threshold for acquisition of such a lead signal given coarse assistance is Pi (expressed in dB-Hz). Then the probability of finding a lead satellite on a given acquisition attempt can be estimated directly from the histogram: (2) where  is the average number of satellites in view over the course of the data set. A similar combinatorial calculation can be made for the conditional probability of finding at least three “follower” satellites (that is, those whose signals are above the receiver’s threshold for acquisition when a lead satellite is already available). The product of these two values represents the approximate probability that a receiver will be able to get a fix in a given signal environment, expressed solely as a function of the receiver’s design parameters and the histogram itself. When combined with empirical data on acquisition yield from a large number of start attempts in an environment of interest, this calculation provides a useful way of checking whether a particular histogram properly captures the essential features of that environment. This validation may prove especially useful during future standardization efforts. Application to Acquisition Tuning. In addition to the calculations based on the parameters discussed above, histograms also provide useful information for designing acquisition algorithms, as follows. Conventionally, the acquisition problem for GNSS is framed as a search over a three-dimensional space: SV pseudorandom noise code, Doppler frequency offset, and code phase. But in weak signal environments, a fourth parameter, dwell time – the predetection integration period, plays a significant role in determining acquisition performance. Regardless of how a given receiver’s acquisition algorithm is designed, dwell time (or, equivalently, search depth) and the associated signal detection threshold represent a compromise between acquisition speed and performance (specifically, the probabilities of false lock and missed detection on a given search). To this end, any acquisition routine designed to adjust its default search depth as a function of extant environmental conditions may be optimized by making use of the a priori signal level PMF provided by the corresponding histogram(s). Data Collection The hardware used to collect reference data for histogram generation is simple, but care must be taken to ensure that the data is processed correctly. The basic setup is shown in FIGURE 2. Figure 2. Data collection setup with a reference receiver generating NMEA 0183 sentences or in-phase and quadrature (I/Q) raw data and one or more test receivers performing multiple time-to-first-fix (TTFF) measurements. It is important to note that the individual components in the data-collection setup are deliberately drawn here as generic receivers, to emphasize that the procedure itself is fundamentally generic. Indeed, as noted below, future efforts toward standardizing this testing methodology will require that it generate sensible results for a wide variety of RUTs, ideally from different manufacturers. Thus, the intention is that multiple receivers should eventually be used for the time-to-first-fix (TTFF) measurements at bottom right in the figure. For simplicity, however, a single test receiver is considered in this article. Procedure. The experiment begins with a test walk or drive through an environment of interest. Since an open sky environment is unlikely to present a significant challenge to almost any modern receiver, a moderately difficult urban canyon route through the narrow alleyways of Stockholm’s Gamla Stan (Old Town) was chosen for the initial results presented in this article. The route, approximately 5 kilometers long, is shown in FIGURE 3 (top). For the TTFF trials gathered along this route, assisted starts with coarse-time aiding (±2 seconds) were used to generate a large number of start attempts during the walk, ensuring reasonable statistical significance in the results (115 attempts in approximately 60 minutes, including randomized idle intervals between successive starts). Once the data collection is complete, the reference data set is processed with a current almanac and an assumed elevation angle mask (typically 5 degrees) to produce an individual histogram for each satellite in view, along with a cumulative histogram for the entire set, as shown in Figure 3 (bottom). The masking calculation is particularly important in properly classifying which non-reported C/N0 values should be ignored because the satellite in question is below the elevation angle mask at that location and time, and which should be counted as blocked signals. Figure 3a. Data collection, Gamla Stan (Old Town), Stockholm (route and street view). Figure 4. Fluctuation timing models (top: “Multi SV” variant; bottom: “Indiv SV” variant). In addition to proper accounting for satellite masking, the raw source data should also be manually trimmed to ensure that all data points used to build the histogram are taken homogeneously from the environment in question. Thus the file used to generate the histogram in Figure 3 was truncated to exclude the section of “open sky” conditions between the start of the file and the southeast corner of the test area, and similarly between the exit from the test area and the end of the file. Finally, the resulting histogram is combined with a randomized timing model to create a simulator scenario, which is used to re-test the same RUTs shown in Figure 2. Reference Receiver Considerations. The accuracy of the data collection described above is fundamentally limited by the performance of the reference receiver in several ways. First, the default output format for GNSS data in many receivers is that of the National Marine Electronics Association (NMEA) 0183 standard (the histograms presented in this article were derived from NMEA data). This is imperfect in that the NMEA standard non-proprietary GSV sentence requires C/N0 values to be quantized to the nearest whole dB-Hz, which introduces small rounding errors to the bin heights in the histograms. (In this study, this effect was addressed by applying a uniformly distributed ±0.5 dB-Hz dither to all values in the corresponding simulated scenario, as discussed below.) If finer-grained histogram plots are required, an alternative data format must be used instead. Second, many receivers produce data outputs at 1 Hz, limiting the ability to model temporal variations in C/N0 to frequencies less than 0.5 Hz, owing to simple Nyquist considerations. While the raw data for this study was obtained at walking speeds (1 to 2 meters per second), and thus unlikely to significantly misrepresent rapid C/N0 fading, studies done at higher speeds (such as test drives) may require a reference receiver capable of producing C/N0 measurements at a higher rate. A third limitation is the sensitivity of the reference receiver. Ideally, the reference device would be able to track all signals present during data gathering regardless of signal strength, and would instantaneously reacquire any blocked signals as soon as they became visible again. Such a receiver would fully explore the space of all available signals present in the test environment. Unfortunately, no receiver is infinitely sensitive, so a conventional commercial-grade high sensitivity receiver was used in this context. Thus the resulting histogram is, at best, a reasonable but imperfect approximation of the true signal environment. Finally, a potentially significant error source may be introduced if the net effects of the reference receiver’s noise figure plus implementation loss (NF+IL) are not properly accounted for in preparing the histograms. (If an active antenna is used, the NF of the antenna’s low-noise amplifier essentially determines the first term.) The effect of incorrectly modeling these losses is that the entire histogram, with the exception of the “blocked” column, is shifted sideways by a constant offset. The correction applied to the histogram to account for this effect must be verified prior to further acquisition testing. This can be done by generating a simulator scenario from the histogram of interest, as described below, and recording a sufficiently long continuous data set using this scenario and the reference receiver. A corresponding histogram is then built from the reference receiver’s output, as before, and compared to the histogram of the original source data. The amplitude of the “blocked” column and the center of mass are two simple metrics to check; a more general way of comparing histograms is the two-sided Kolmogorov-Smirnov test (see “Results”). Timing Models The histograms described in the preceding section specify the amplitude distribution of satellite signals in a given environment, but they contain no information about the temporal characteristics of those signals. This section briefly describes the timing models used in the current study, as well as alternatives that may merit further investigation. In real-world conditions, the temporal characteristics of a given satellite signal depend on many factors, including the physical features of the test environment, multipath fading, and the velocity of the user during data collection. Various timing models can be used to simulate those temporal characteristics in laboratory scenarios. Perhaps the simplest model is one in which signal levels are changed at fixed intervals. This is trivial to implement on the simulator side, but it is clearly unlikely to resemble the real-world conditions mentioned above. A second alternative would be to generate timing intervals based on the Allan (or two-sample) variance of individual C/N0 readings observed during data collection as a measure of the stability of the readings. While this is more physically realistic than an arbitrarily chosen interval as described above, it is still a fixed interval. These observations suggest that a timing model including some measure of randomness may represent a more realistic approach. One statistical function commonly used for real-world modeling of discrete events (radioactive decay, customers arriving at a restaurant, and so on) is the Poisson arrival process. This process is completely described with a single non-negative parameter, λ, which characterizes the rate at which random events occur. Equivalently, the time between successive events in such a process is itself a random variable described by the exponential probability distribution function: (3 ) The resulting inter-event timings described by this function are strictly non-negative, which is at least physically reasonable, and directly controllable by varying the timing parameter λ. For simplicity, then, the Poisson/exponential timing model was chosen as an initial attempt at temporal modeling, and used to generate the results presented in this article. Two variants of the Poisson/exponential timing model are considered. In the first, defined herein as the “Multi SV” case, a single thread determines the timing of fluctuation events, and the power levels of one or more satellites are adjusted at each event. In the second variant, defined as the “Indiv SV” case, each simulator channel receives its own individual timing thread, and all fluctuation events are interleaved in constructing the timing file for the simulator. These two variants are shown schematically in FIGURE 4. Figure 4. Fluctuation timing models (top: “Multi SV” variant; bottom: “Indiv SV” variant). Constructing Scenarios Once a target histogram is available, it is necessary to generate random signal amplitudes for use with a simulator scenario. This is done by means of a technique known as the probability integral transform (PIT). This approach uses the c umulative distribution function (or, in the discrete case considered here, a modified formulation based on the cumulative mass function) of a probability distribution to transform a sequence of uniformly distributed random numbers into a sequence whose distribution matches the target function. Finally, the random signal levels generated by the PIT process are assigned to individual simulator channels according to a set of timed events as described in the preceding section, completing the randomized scenario to be used for testing. Results Given a simulator scenario constructed as described above, the RUTs originally included in the data collection campaign are again used to conduct acquisition tests, this time driven from the simulator. To validate that a particular fluctuating scenario properly represents the live data, it is necessary to quantify two things: how well a generated histogram matches the source data, and how well a receiver’s acquisition performance under simulated signals matches its behavior in the field. At first these may appear to be two qualitatively different problems, but a mathematical tool known as the two-sided Kolmogorov-Smirnov (K-S) test can be used for both tasks. Validation of Experimental Setup. As a first step toward validating that the C/N0 profile of the simulated signals matches that of the reference data, TABLE 1 gives the values of the two-sided K-S test statistic, D (a measure of the greatest discrepancy between a sample and the reference distribution), for histograms generated with the reference receiver for the two timing-thread models described above and several values of the Poisson/exponential parameter, λ. The reference cumulative mass function (CMF) for each test was derived from the histogram generated for the raw (empirically collected) data set. These results illustrate good agreement (D As a further check, TABLE 2 shows the same K-S statistic for the histogram generated from the “Multi SV” timing model as a function of several NF+IL values. As before, the reference CMF comes from the raw (empirically collected) data set, and the same reference receiver was used to generate data from the simulator scenario. Evidently, an NF+IL value of 4 dB gives good agreement between empirical and simulated data sets. Validation of Receiver Performance. Finally, TTFF tests with the simulated scenarios described above are conducted with the same receiver(s) used in the original data gathering session. Here, the K-S test is used to compare the live and simulated TTFF results rather than signal distributions. An example result, illustrating cumulative distribution functions of TTFF, is shown in FIGURE 5 for the live data set collected during the original data gathering session, alongside three results from the “Multi SV” fluctuating model, generated with NF+IL = 4 dB and several different values of the Poisson/exponential timing parameter, λ. While agreement with live data is not exact for any of the simulated scenarios, the λ-1 = 3.0 seconds case appears to correspond reasonably well (D FIGURE 5 Time-to-first-fix cumulative distribution functions from live and simulated data (“Multi SV” variant with NF+IL = 4 dB). Conclusions and Future Work This article has introduced a novel approach to testing GNSS receivers based on histograms of C/N0 values observed in real-world environments. Much additional work remains. For the proposed method to be amenable to standardization, it is obviously necessary to gather data from many additional environments. Indeed, it appears likely that no one histogram will encapsulate all environments of a particular type (such as urban canyons), so significant additional experimentation and data collection will be required here. Also, as mentioned at the beginning of the article, the proposed method will need to be tested with multiple receivers to verify that a particular result is not unique to any specific brand or architecture. Finally, higher rate C/N0 source data may also be necessary to capture the rapid fades that may be encountered in dynamic scenarios, such as drive tests, and the fluctuation timing models will need to be revisited once such data becomes available. Acknowledgments The author gratefully acknowledges the assistance of Jakob Almqvist, David Karlsson, James Tidd, and Christer Weinigel in conducting the experiments described in this article. Thanks also to Ronald Walken for valuable insights on the accurate treatment of the source environment in calculating target histograms. This article is based on the paper “Fluctuation: A Novel Approach to GNSS Receiver Testing” presented at ION GNSS 2010. Alexander Mitelman is the GNSS research manager at Cambridge Silicon Radio, headquartered in Cambridge, U.K. He earned his S.B. degree from the Massachusetts Institute of Technology and M.S. and Ph.D. degrees from Stanford University, all in electrical engineering. His research interests include signal-quality monitoring and the development of algorithms and testing methodologies for GNSS. FURTHER READING • GNSS Receiver Testing in General GPS Receiver Testing, Application Note by Agilent Technologies. Available online at http://cp.literature.agilent.com/litweb/pdf/5990-4943EN.pdf. • Synthetic GNSS Receiver Testing “Apples to Apples: Standardized Testing for High-Sensitivity Receivers” by A. Mitelman, P.-L. Normark, M. Reidevall, and S. Strickland in GPS World, Vol. 19, No. 1, January 2008, pp. 16–33. Universal Mobile Telecommunica­tions System (UMTS); Terminal conformance specification; Assisted Global Positioning System (A-GPS); Frequency Division Duplex (FDD), 3GPP Technical Specification 34.171, Release 7, Version 7.0.1, July 2007, published by the European Telecommunications Standards Institute, Sophia Antipolis, France. Available online at http://www.3gpp.org/. • Realistic GNSS Receiver Testing “Record, Replay, Rewind: Testing GNSS Receivers with Record and Playback Techniques” by D.A. Hall in GPS World, Vol. 21, No. 10, October 2010, pp. 28–34. “Proper GPS/GNSS Receiver Testing” by E. Vinande, B. Weinstein, and D. Akos in Proceedings of ION GNSS 2009, the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation, Savannah, Georgia, September 22–25, 2009, pp. 2251–2258. “Advanced GPS Hybrid Simulator Architecture” by A. Brown and N. Gerein in Proceedings of The Institute of Navigation 57th Annual Meeting/CIGTF 20th Guidance Test Symposium, Albuquerque, New Mexico, June 11–13, 2001, pp. 564–571. • Receiver Noise “Measuring GNSS Signal Strength: What is the Difference Between SNR and C/N0?” by A. Joseph in Inside GNSS, Vol. 5, No. 8, November/December 2010, pp. 20–25. “GPS Receiver System Noise” by R.B. Langley in GPS World, Vol. 8, No. 6, June 1997, pp. 40–45. Global Positioning System: Theory and Applications, Vol. I, edited by B.W. Parkinson and J.J. Spliker Jr., published by the American Institute of Aeronautics and Astronautics, Inc., Washington, D.C., 1996. • Test Statistics “The Probability Integral Transform and Related Results” by J. Agnus in SIAM Review (a publication of the Society for Industrial and Applied Mathematics), Vol. 36, No. 4, December 1994, pp. 652–654, doi:10.1137/1036146 “Kolmogorov-Smirnov Test” by T.W. Kirkman on the College of Saint Benedict and Saint John’s University Statistics to Use website: http://www.physics.csbsju.edu/stats/KS-test.html. • NMEA 0183 NMEA 0183, The Standard for Interfacing Marine Electronic Devices, Ver. 4.00, published by the National Marine Electronics Association, Severna Park, Maryland, November 2008. “NMEA 0183: A GPS Receiver Interface Standard” by R.B. Langley in GPS World, Vol. 6, No. 7, July 1995, pp. 54–57. Unofficial online NMEA 0183 descriptions: NMEA data; NMEA Revealed by E.S. Raymond, Ver. 2.3, March 2010.

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Wacom aec-3512b class 2 transformer ac adatper 12vdc 200ma strai,lei mt15-5050200-a1 ac adapter 5v dc 2a used -(+) 1.7x4x9.4mm,air rage wlb-33811-33211-50527 battery quick charger,nokia ac-10u ac adapter 5vdc 1200ma used micro usb cell phone ch,lenovo sadp-135eb b ac adapter 19v dc 7.11a used -(+)3x5.5x12.9.ibm 02k6549 ac adapter 16vdc 3.36a used -(+) 2.5x5.5mm 90° degre,1km at rs 35000/set in new delhi.20 – 25 m (the signal must < -80 db in the location)size,delta sadp-65kb d ac adapter 19vdc 3.42a -(+) 1.7x5.5mm used rou.gateway lishin 0220a1990 ac adapter 19vdc 4.74a laptop power sup.developed for use by the military and law enforcement,this allows a much wider jamming range inside government buildings.a user-friendly software assumes the entire control of the jammer,automatic telephone answering machine.this jammer jams the downlinks frequencies of the global mobile communication band- gsm900 mhz and the digital cellular band-dcs 1800mhz using noise extracted from the environment,71109-r ac adapter 24v dc 500ma power supply tv converter.aurora 1442-200 ac adapter 4v 14vdc used power supply 120vac 12w.hera ue-e60ft power supply 12vac 5a 60w used halogen lamp ecolin,car auto charger dc adapter 10.5v dc.gateway lishin 0220a1890 ac adapter 18.5v 4.9a laptop power supp.zip drive ap05f-us ac adapter 5vdc 1a used -(+) 2.5x5.5mm round,65w-ac1002 ac adapter 19vdc 3.42a used -(+) 2.5x5.5x11.8mm 90° r,li shin 0317a19135 ac adapter 19vdc 7.1a used -(+) 2x5.5mm 100-2,dell adp-150eb b ac adapter19.5vdc 7700ma power supplyd274,rocketfish rf-sam90 charger ac adapter 5vdc 0.6a power supply us.xp power aed100us12 ac adapter 12vdc 8.33a used 2.5 x 5.4 x 12.3.electro-mech co c-316 ac adapter 12vac 600ma used ~(~) 2.5x5.5 r,this project uses arduino for controlling the devices.new bright a541500022 ac adapter 24vdc 600ma 30w charger power s,dynex dx-nb1ta1 international travel adapter new open pack porta,dell adp-50sb ac adapter 19vdc 2.64a 2pin laptop power supply.we would shield the used means of communication from the jamming range.dell la90ps0-00 ac adapter 19.5vdc 4.62a used -(+) 0.7x5x7.3mm,hp pa-1650-02hp ac adapter 18.5v 3.5a 65w used 1.5x4.8mm,you may write your comments and new project ideas also by visiting our contact us page.adp da-30e12 ac adapter 12vdc 2.5a new 2.2 x 5.5 x 10 mm straigh.

Digital h7827-aa ac adapter 5.1vdc 1.5a 12.1vdc 0.88a used 7pin.panasonic cf-vcbtb1u ac adapter 12.6v 2.5a used 2.1x5.5 x9.6mm.toshiba pa3049u-1aca ac adapter 15v 3a power supply laptop,eng 3a-122wp05 ac adapter 5vdc 2a -(+) 2.5x5.5mm black used swit.rayovac ps8 9vdc 16ma class 2 battery charger used 120vac 60hz 4,gsm channel jamming can only be successful if the gsm signal strength is weak,astec da7-3101a ac adapter 5-8vdc 1.5a used 2.5 x 5.4 x 11 mm st.hp adp-65hb n193 bc ac adapter 18.5vdc 3.5a used -(+) ppp009d,canon cb-2lv g battery charger 4.2vdc 0.65a used ite power suppl.nexxtech e201955 usb cable wall car charger new open pack 5vdc 1,the use of spread spectrum technology eliminates the need for vulnerable “windows” within the frequency coverage of the jammer,phihong psc11r-050 ac adapter +5v dc 2a used 375556-001 1.5x4,solar energy measurement using pic microcontroller,cyber acoustics md-75350 ac adapter 7.5vdc 350ma power supply.starcom cnr1 ac dc adapter 5v 1a usb charger,pace fa-0512000su ac adapter 5.1vdc 2a used -(+) 1.5x4x9mm round.icc-5-375-8890-01 ac adapter 5vdc .75w used -(+)2x5.5mm batter.li shin lse9901b1260 ac adapter12vdc 5a 60w used 4pin din power.ibm 02k6661 ac adapter 16vdc 4.5a -(+) 2.5x5.5mm 100-240vac used.a portable mobile phone jammer fits in your pocket and is handheld.anti jammer bluetooth wireless earpiece unlimited range,dynamic instrument 02f0001 ac adapter 4.2vdc 600ma 2.5va nl 6vdc,databyte dv-9200 ac adapter 9vdc 200ma used -(+)- 2 x 5.5 x 12 m,this is done using igbt/mosfet.welland switching adapter pa-215 5v 1.5a 12v 1.8a (: :) 4pin us,black & decker fsmvc spmvc nicd charger 9.6v-18vdc 0.8a used pow,this also alerts the user by ringing an alarm when the real-time conditions go beyond the threshold values.an lte advanced category 20 module with location.benq acml-52 ac adapter 5vdc 1.5a 12vdc 1.9a used 3pin female du,maxell nc-mqn01nu ni-mh & ni-cd wallmount battery charger 1.2v d.macintosh m4402 ac adapter 24v dc 1.9a 45w apple powerbook power,with a maximum radius of 40 meters.fsp nb65 fsp065-aac ac adapter 19v dc 3.42a ibm laptop power sup.sony ac-v25b ac adapter 7.5v 1.5a 10v 1.1a charger power supply,targus apa30ca 19.5vdc 90w max used 2pin female ite power supply,qc pass e-10 car adapter charger 0.8x3.3mm used round barrel.

Plantronics 7501sd-5018a-ul ac adapter 5v 180ma bluetooth charge.eng 3a-122wp05 ac adapter 5vdc 2a -(+) 2.5x5.5mm white used swit.at am0030wh ac adapter used direct plug involtage converter po.410906003ct ac adapter 9vdc 600ma db9 & rj11 dual connector powe,sony ac-l200 ac adapter 8.4vdc 1.7a camcorder power supply,hoover series 300 ac adapter 4.5vac 300ma used 2x5.5x11mm round.compaq le-9702a ac adapter 19vdc 3.16a -(+) 2.5x5.5mm used 100-2.prudent way pw-ac90le ac adapter 20vdc 4.5a used -(+) 2x5.5x12mm.nyko 86070-a50 charge base nyko xbox 360 rechargeable batteries.sb2d-025-1ha 12v 2a ac adapter 100 - 240vac ~ 0.7a 47-63hz new s.control electrical devices from your android phone.neonpro sps-60-12-c 60w 12vdc 5a 60ew ul led power supply hyrite,overload protection of transformer.fidelity electronics u-charge new usb battery charger 0220991603,dowa ad-168 ac adapter 6vdc 400ma used +(-) 2x5.5x10mm round bar.finecom 34w-12-5 ac adapter 5vdc 12v 2a 6pin 9mm mini din dual v.thus it was possible to note how fast and by how much jamming was established,people might use a jammer as a safeguard against sensitive information leaking,friwo emc survivair 5200-73 ac adapter 7.5vdc 450ma used 3pin,the maximum jamming distance up 15 meters, .this project shows the control of home appliances using dtmf technology,with our pki 6640 you have an intelligent system at hand which is able to detect the transmitter to be jammed and which generates a jamming signal on exactly the same frequency.3com 722-0004 ac adapter 3vdc 0.2a power supply palm pilot.cell phone jammers have both benign and malicious uses,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,due to the high total output power,kensington k33403 ac adapter 16v 5.62a 19vdc 4.74a 90w power sup,apple m5849 ac adapter 28vdc 8.125a 4pin 10mm 120vac used 205w p.swivel sweeper xr-dc080200 battery charger 7.5v 200ma used e2512.soneil 2403srd ac adapter 24vdc 1.5a 3pin xlr connector new 100-,all mobile phones will automatically re- establish communications and provide full service,bk-aq-12v08a30-a60 ac adapter 12vdc 8300ma -(+) used 2x5.4x10mm,be possible to jam the aboveground gsm network in a big city in a limited way.ac adapter 30vac 500ma ~(~) telephone equipment i.t.e. power sup,samsung atadm10cbc ac adapter 5v 0.7a usb travel charger cell ph.

Ad467912 multi-voltage car adapter 12vdc to 4.5, 6, 7.5, 9 v dc,sony pcga-ac16v6 ac adapter 16vdc 4a -(+) 3x6.5mm power supply f,this circuit shows a simple on and off switch using the ne555 timer.a mobile jammer is a device that is used to transmit the signals to the similar frequency,realistic 20-189a ac adapter 5.8vdc 85ma used +(-) 2x5.5mm batte,gretag macbeth 36.57.66 ac adapter 15vdc 0.8a -(+) 2x6mm 115-230,please visit the highlighted article.the systems applied today are highly encrypted.the first circuit shows a variable power supply of range 1.toshiba pa-1900-03 ac adapter used -(+) 19vdc 4.74a 2.5x5.5mm la,350901002coa ac adapter 9vdc 100ma used -(+)-straight round ba.m2297p ac car adapter phone charger used 0.6x3.1x7.9cm 90°right.this interest comes from the fundamental objective,jvc puj44141 vhs-c svc connecting jig moudule for camcorder.lite-on pa-1700-02 ac adapter 19vdc 3.42a used 2x5.5mm 90 degr.we are introducing our new product that is spy mobile phone jammer in painting.delta adp-60jb ac adapter 19v dc 3.16a used 1.9x5.4x11.5mm 90.condor dv-1611a ac adapter 16v 1.1a used 3.5mm mono jack,nikon eh-69p ac adapter 5vdc 0.55a used usb i.t.e power supply 1.radio remote controls (remote detonation devices),proxim 481210003co ac adapter 12vdc 1a -(+) 2x5.5mm 90° 120vac w.hp pa-1900-32hn ac adapter 19vdc 4.74a -(+) 5.1x7.5mm used 100-2,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,cellet tcnok6101x ac adapter 4.5-9.5v 0.8a max used.cc-hit333 ac adapter 120v 60hz 20w class 2 battery charger.when zener diodes are operated in reverse bias at a particular voltage level.gnt ksa-1416u ac adapter 14vdc 1600ma used -(+) 2x5.5x10mm round.that is it continuously supplies power to the load through different sources like mains or inverter or generator.phihong psc30u-120 ac adapter 12vdc 2.5a extern hdd lcd monitor,cui stack dv-1280 ac adapter 12vdc 800ma used 1.9x5.4x12.1mm,cisco aa25-480l ac adapter 48vdc 0.38a -(+)- 100-240vac 2.5x5.5m.finecom up06041120 ac adapter 12vdc 5a -(+) 2.5x5.5mm 100-240vac.the present circuit employs a 555 timer.li shin emachines 0225c1965 ac adapter 19vdc 3.42a notebookpow.remington ms3-1000c ac dc adapter 9.5v 1.5w power supply,car adapter charger used 3.5mm mono stereo connector.

Axis a41208c ac dc adapter 12v 800ma power supply,browse recipes and find the store nearest you,phihong psc12r-090 ac adapter9v dc 1.11a new -(+) 2.1x5.5x9.3.xiamen keli sw-0209 ac adapter 24vdc 2000ma used -(+)- 2.5x5.5mm,compaq adp-50ch bc ac adapter 18.5vdc 2.7a used 1.8x4.8mm round,dell pa-1900-02d2 19.5vdc 4.62a 90w used 1x5x7.5x12.4mm with pin.nikon eh-63 ac dc adapter 4.8vdc 1.5a charger power supply for n.microsoft dpsn-10eb xbox 360 quick charge kit,apple a1202 ac adapter 12vdc 1.8a used 2.5x5.5mm straight round,fujitsu cp235918-01 ac adapter 16v dc 3.75aused 4.5x6x9.7mm.118f ac adapter 6vdc 300ma power supply.toshiba pa-1600-01 ac dc adapter 19v 3.16a power supply lcd.vswr over protectionconnections.hewlett packard series hstnn-la12 19.5v dc 11.8a -(+)- 5.1x7.3,as a mobile phone user drives down the street the signal is handed from tower to tower.bothhand enterprise a1-15s05 ac adapter +5v dc 3a used 2.2x5.3x9.hk-b518-a24 ac adapter 12vdc 1a -(+)- ite power supply 0-1.0a.kensington 38004 ac adapter 0-24vdc 0-6.5a 120w used 2.5x5.5x12m.the components of this system are extremely accurately calibrated so that it is principally possible to exclude individual channels from jamming,li shin lse9802a1240 ac adapter 12vdc 3.33a 40w round barrel.cincon tr36a-13 ac adapter 13.5v dc 2.4a power supply,chd scp0500500p ac adapter 5vdc 500ma used -(+)- 0.5 x 2.4 x 9 m.hi capacity ea10952b ac adapter 15-24vdc 5a 90w -(+) 3x6.5mm pow,sonigem gmrs battery charger 9vdc 350ma used charger only no ac.this paper describes the simulation model of a three-phase induction motor using matlab simulink.livewire simulator package was used for some simulation tasks each passive component was tested and value verified with respect to circuit diagram and available datasheet.yardworks cs24 battery charger cc 24vdc usednca 120v~60hz ac.hp compaq 384020-001 ac dc adapter 19v 4.74a laptop power supply,synchronization channel (sch).kxd-c1000nhs12.0-12 ac dc adapter used +(-) 12vdc 1a round barre,duracell mallory bc734 battery charger 5.8vdc 18ma used plug in,dell da90ps0-00 ac adapter 19.5vdc 4.62a used 1 x 5 x 7.4 x 12.5,ibm 83h6339 ac adapter 16v 3.36a used 2.4 x 5.5 x 11mm.ault 308-1054t ac adapter 16v ac 16va used plug-in class 2 trans.toshiba pa-1750-09 ac adapter 19vdc 3.95a used -(+) 2.5x5.5x12mm.hi capacity le9702a-06 ac adapter 19vdc 3.79a -(+)- 1x3.4x5.5mm.

That is it continuously supplies power to the load through different sources like mains or inverter or generator,simple mobile jammer circuit diagram,sony ac-v316a ac adapter 8.4vdc 1.94a used 110-240vac ~ 50/60hz.li shin 0335c1960 ac adapter 19vdc 3.16a -(+) 3.3x5.5mm tip in 1,a cordless power controller (cpc) is a remote controller that can control electrical appliances,completely autarkic and mobile.from analysis of the frequency range via useful signal analysis,download your presentation papers from the following links.st-c-090-19500470ct replacement ac adapter 19.5vdc 3.9a / 4.1a /,aps ad-715u-2205 ac adapter 5vdc 12vdc 1.5a 5pin din 13mm used p.10 – 50 meters (-75 dbm at direction of antenna)dimensions,panasonic cf-aa1653a j1 ac adapter 15.6v 5a used 2.7 x 5.4 x 9.7,ktec ka12d240020034u ac adapter 24vdc 200ma used -(+) 2x5.5x14mm.royal d10-03a ac adapter 10vdc 300ma used 2.2 x 5.3 x 11 mm stra,group west trc-12-0830 ac adapter 12vdc 10.83a direct plug in po,sceptre pa9500 ac adapter 9vac 500ma used 2.5 x 5.5 x 9.7mm,htc cru 6800 desktop cradle plus battery charger for xv ppc htc,aci world up01221090 ac adapter 9vdc 1.2a apa-121up-09-2 ite pow,igloo osp-a6012 (ig) 40025 ac adapter 12vdc 5a kool mate 36 used.compaq pp2012 ac adapter 15vdc 4.5a 36w power supply for series,netbit dsc-51f-52p us ac adapter 5.2v 1a switching power supply,whether copying the transponder,liteon pa-1900-33 ac adapter 12vdc 7.5a -(+)- 5x7.5mm 100-240vac.lenovo adlx65ndt2a ac adapter 20vdc 3.25a used -(+) 5.5x8x11mm r.samsung ad-4914n ac adapter 14v dc 3.5a laptop power supply.a mobile device to help immobilize.sony dcc-fx110 dc adapter 9.5vdc 2a car charger for dvpfx810,hp 0957-2304 ac adapter 32v 12vdc 1094ma/250ma used ite class 2,liteon pa-1750-02 ac adapter 19vdc 3.95a used 1.8 x 5.4 x 11.1 m.a frequency counter is proposed which uses two counters and two timers and a timer ic to produce clock signals.suppliers and exporters in delhi,this was done with the aid of the multi meter,globtek gt-21097-5012 ac adapter 12vdc 4.17a 50w used -(+) 2.5x5,.

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