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Photo: Mark L. Psiaki, Brady W. O’Hanlon, Steven P. Powell, Jahshan A. Bhatti, Todd E. Humphreys, and Andrew Schofield Spoofing Detection with Two-Antenna Differential Carrier Phase By Mark L. Psiaki, Brady W. O’Hanlon, Steven P. Powell, Jahshan A. Bhatti, Todd E. Humphreys, and Andrew Schofield A new method detects spoofing attacks that are resistant to standard RAIM technique and can sense an attack in a fraction of a second without external aiding. The signal-in-space properties used to detect spoofing are the relationships of the signal arrival directions to the vector that points from one antenna to the other. A real-time implementation succeeded against live-signal spoofing attacks aboard a superyacht, the White Rose of Drachs shown above, cruising in international waters. Read more about “Red Team, White Team, Blue Team” below. Concerns about spoofing of open-service GNSS signals inspired early work on simple receiver-autonomous integrity monitoring (RAIM) methods based on the consistency of the navigation solution. Work on new classes of defense techniques began in earnest after the demonstration of a powerful spoofer that is undetectfable by simple pseudorange-based RAIM methods. There has been a sense of urgency to solve the spoofing problem since the Iranians captured a classified U.S. drone in 2011 and made unsubstantiated claims to have spoofed its GPS. Two dramatic field demonstrations of the spoofer developed by author Humphreys and colleagues at the University of Texas, Austin, heightened interest in spoofing detection: one involved deception of a small airborne unmanned autonomous vehicle (UAV), causing it to dive towards the ground; another sent a superyacht off course without raising any alarms on its bridge. One class of spoofing detection methods uses encrypted signals, their known relationships to the open-service signals, and after-the-fact availability of encryption information. Such techniques require a high-bandwidth communication link between the potential victim of a spoofing attack and a trusted source of after-the-fact encryption information, and may involve significant latency between attack and detection. Another class of methods uses advanced RAIM-type techniques. Instead of considering only pseudorange consistency, these RAIM techniques examine additional signal characteristics such as absolute power levels, distortion of the PRN code correlation function along the early/late axis, the possible existence of multiple distinct correlation peaks in signal-acquisition-type calculations, and other signal or receiver characteristics. Such methods are relatively simple to implement because they do not require much additional hardware, if any, but some of these strategies can have trouble distinguishing between multipath and spoofing or between jamming and spoofing. A third class proposes the addition of Navigation Message Authentication bits. These are encrypted parts of the low-rate navigation data message. Such techniques require modification of the navigation data message and can allow long latencies between the onset of a spoofing attack and its detection. A fourth class exploits the differing signal-in-space geometry of spoofed signals in comparison to true GNSS signals. All spoofed signals typically arrive from the same direction, but true signals arrive from a multiplicity of directions. Some of these methods use receiver antenna motion to achieve direction-of-arrival sensitivity. Others use an array of two or more receiver antennas. The most powerful of these detection strategies exploit models of the effects on carrier-phase data of antenna motion or antenna-array geometry. This knowledge may be partial because an unknown antenna-array attitude may need to be determined as part of the detection calculation. Their power derives from the high degree of accuracy with which a typical GNSS receiver can measure beat carrier phase. Goals. This research follows on moving-antenna/carrier-phase-based spoofing detection work. One of our goals has been to remove the necessity for moving parts by using two antennas and processing their carrier-phase data. A second goal has been to achieve real-time operation. An earlier prototype moving-antenna system (see “GNSS Spoofing Detection,” GPS World, June 2013) used post-processing and completed its spoofing detection calculations days or weeks after the recording of wide-band RF data during live-signal attacks. A third goal has been to test this system against actual live-signal spoofing attacks to prove its real-time capabilities and evaluate its performance during the two phases of an attack: the initial signal capture and the post-capture drag-off to erroneous position and timing fixes. Two-Antenna System Architecture The system consists of two GNSS patch antennas, GPS receiver hardware and software, and spoofing detection signal-processing hardware and software. Figure 1 shows two versions. The left-hand version connects its two patch antennas to an RF switch. The single analog RF output of the switch is input to a GNSS receiver that is standard in all respects, except for two features. First, it controls the RF switch or, at least, has access to the switching times. Second, it employs a specialized phase-locked loop (PLL) that can track the beat carrier phase of a given signal through the phase jumps that occur at the switching times. The right-hand version connects each antenna to an independent GPS receiver, likely connected to a common reference oscillator. Figure 1. Two configurations:, the RF-switched-signal/single-receiver configuration (left) and the two-receiver configuration (right). The last element of each system is a spoofing detection signal-processing unit. Its inputs are the single-differenced beat carrier phases of all tracked signals, with differences taken between the two antennas. In the switched antenna system, each difference is deduced by the specialized PLL. In the two-receiver system, the single-differences are calculated explicitly from each receiver’s beat carrier-phase observables. Except for the final spoofing detection unit, the two-receiver system on the right-hand side of Figure 1 is already available commercially. Typical applications are CDGPS-based attitude/heading determination. Thus, this is the easiest version to implement. This system could include more than two antennas. A multi-antenna system could have a dedicated RF front-end and a dedicated set of receiver channels for each antenna, as on the right of Figure 1. Alternatively, a multi-antenna system could include an RF switch between any one of the multiple antennas at the command of the receiver. The latter design would entail a slight modification to the specialized PLL to track multiple independent phase jumps for the independent antenna switches. Principles. The principles used to detect spoofing can be understood by considering and comparing the signal-in-space and antenna geometries shown in Figure 2, the two-antenna system and three GNSS satellites for a typical non-spoofed case, and Figure 3, a spoofed case. The salient difference is that the different GNSS signals arrive from different directions for the non-spoofed case, namely and . They all arrive from the same direction, the direction of the spoofer , for the spoofed case. For detection purposes, the important geometric feature is the projection of each direction of arrival onto the known separation vector between the two antennas, bBA. This projection has a direct effect on the beat carrier-phase difference between the two antennas. In the non-spoofed case, this effect will vary between the different received signals in ways consistent with the attitude of the vector. In the spoofed case, all of these carrier-phase differences will be identical. The spoofing detection algorithm decides between two hypotheses about the carrier-phase differences, one conjecturing a diversity consistent with authentic signals and the other conjecturing the sameness that is characteristic of spoofed signals. Figure 2. Geometry of two-antenna spoofing detection system and GNSS satellites for non-spoofed case. Figure 3. Spoofed-case geometry of two-antenna spoofing detection system and GNSS spoofer. Hypothesis Test The PDF paper on which this article is based presents the non-spoofed and spoofed signal models that form the basis of a hypothesis test, develops optimal estimation algorithms that fit the observed differential beat carrier phases to the two models, and shows how these estimates and their associated fit error costs can be used to develop a sensible spoofing detection hypothesis test. Download the PDF here. Offline and Live-Signal Testing We tested a prototype version of the two-antenna system as depicted on the righthand side of Figure 1. The antennas connect to two independent RF front-ends that run off of the same reference oscillator. These RF front-ends provide input to two independent receivers that track each signal using a delay-lock loop (DLL) and a PLL. Figures 4 and 5 show system elements: two GPS patch antennas mounted on a single ground plane with a spacing of 0.14 meters, two RF front-ends — universal software radio peripherals (USRPs) — with a common ovenized crystal oscillator. Digital signal-processing functions are implemented in real-time software radio receivers (SWRX) running in parallel on a Linux laptop, written in C++. Spoofing detection calculations are performed on the same laptop using algorithms encoded in Matlab. Figure 4. The two antennas of the prototype spoofing detection system mounted on a common ground plane. Figure 5. Signal processing hardware of the prototype spoofing detection system. A key feature of this architecture is the ability of its real-time software radios’ C++ code to call the spoofing detector’s Matlab tic function and to pass carrier-phase and other relevant data to the tic function. This feature served to shorten the implementation and test cycle for the prototype system by eliminating the need to translate the original Matlab versions of the spoofing detection algorithms into C++. This enabled rapid re-tuning and redesign of the spoofing detection calculations, exploited during the course of live-signal testing. The Matlab package displays real-time signal authentication information. Figure 6 shows the version of the display used for this study’s culminating live-signal tests. All displays are updated in real time. The upper left, upper right, and lower left plots scroll along their horizontal time axes to keep the most recent 4.5 minutes of data available. The lower right compass updates each time a new spoofing detection calculation is performed. The green dots in the upper left plot indicate that the time between spoofing detections, Δtspf , is nominally 1 second, though sometimes the gap is longer due to lack of a sufficient number of validated single-differenced carrier phases to carry out the calculation. Thus, the nominal update time for all of the plots in this display is 1 second. Faster updates are possible with the Matlab software, but Δtspf was deemed sufficiently fast for this study’s experiments. The most important panel in Figure 6 is the upper left spoofing detection statistic time history. The magenta plus signs on the plot show the spoofing detection threshold chosen for this case, γth. The computed γ values are plotted as green o’s if they lie above γth and as red asterisks if they lie below. If γ is above γth, the message “GPS Signals Authenticated” is displayed on the plot; if below, the message switches to the spoofing alert: “GPS SPOOFING ATTACK DETECTED!” Figure 6. Spoofing detector real-time display. Clockwise from top left: the spoofing detection statistic time history γ(t); four diagnostic time histories that include time histories of the number of satellites used for spoofing detection L(t) (blue asterisks), their corresponding GDOP(t) values (magenta o’s), the time increment between spoofing detection tests Δtspf(t) (green dots), and the compass heading ψ(t) as determined from the two-antenna non-spoofed-case solution (black dots); Compass display; and time history of GPS PRN number availability. The other three panels proved helpful in diagnosing system performance. A low L value (near 4) or a high GDOP value in the upper right panel indicated poorer reliability of the spoofing detection calculations. A correct compass heading in the absence of spoofing provided a check on the system. During spoofing attacks, the compass heading became jumpy, thereby providing another possible indicator of inauthentic signals. The vertical scale of the lower left panel lists the possible GPS PRN numbers. The presence of a green or red dot at the level corresponding to a given PRN number indicates that one or both receivers is seeing something from that satellite at the corresponding time. If the dot is red, then the returned data are incomplete or are deemed to be insufficiently validated for use in the spoofing detection calculation. If the dot is green, then the data from that PRN have been used in the detection that has been carried out at that time. Another feature of the prototype spoofing detection system is its ability to record the wide-band RF data from its two antennas. For each spoofing scenario, the raw samples from both USRPs were recorded while the real-time software receiver was performing its signal-processing operations and while the real-time spoofing detector was doing its calculations. These recorded data streams will allow off-line analysis and testing of a re-tuned or completely redesigned spoofing detection system. Red Team Receiver/Spoofer. The UT Austin spoofer’s attack strategy overlays the spoofed signal on top of the true signals, ramps up the power to capture the receiver tracking loops, and finally drags the pseudorange, beat carrier phase, and carrier Doppler shift off from their true values to spoofed values. Figure 7 shows the pseudorange part of a spoofing attack: cross-correlation of the receiver’s PRN code replica with the total received signal (blue solid curve); the receiver’s early, prompt, and late correlations (red dots); and the spoofer signal (black dash-dotted curve). In the top plot, the spoofer has zero power, and the receiver sees only the true signal. The second and third plots show the spoofer ramping up its power while maintaining its false signal in alignment with the true signal. The spoofer power in the middle/third plot is sufficient to capture control of the three red dots of the receiver’s DLL. In the fourth and fifth plots, the spoofer initiates and continues a pseudorange drag-off, an intentional falsification of the pseudorange as measured by the victim receiver’s DLL. Figure 7. Receiver/spoofer attack sequence as viewed from a channel’s code offset cross-correlation function. Spoofer signal: black dash-dotted curve; sum of spoofer and true signals: blue solid curve; receiver early, prompt, and late correlation points: red dots. The spoofer performs drag-off simultaneously on all spoofed channels in a vector spoofing attack that maintains consistency of all spoofed pseudoranges. After the initiation of drag-off, the victim receiver computes a wrong position, a wrong true time, or both, but the residual pseudorange errors in its navigation solution remain small. Therefore, this type of attack is not detectable by traditional pseudorange-based RAIM calculations. The receiver spoofer hardware consists of a GNSS reception antenna, the receiver spoofer signal-processing unit, and the spoofer transmission antenna (Figure 8). Figure 8a. Receiver/spoofer hardware: GPS reception antenna on ship’s rear upper deck. Figure 8b. Receiver/spoofer hardware: directional transmission antenna pointed at the ship’s GPS antenna and the detector antenna pair near the defended ship’s antenna. The orientation of the spoofing transmission antenna, combined with its remote location from the receiver/spoofer’s reception antenna, ensured that the spoofer did not self-spoof. Figure 8c. Receiver/spoofer hardware: spoofer electronics, located amidships. The receiver/spoofer requires tuning of its transmission power levels. If the power is too high, its spoofing attacks will be too obvious. A very high transmitted power could also saturate the front-end electronics of the intended victim, causing it to jam the system rather than spoof it. If transmitted power is too low, it will not capture the victim’s tracking loops, and its spoofing attack will fail. The proper power level depends on the gain patterns of the spoofer transmission antenna and the victim receiver antenna and on their relative geometry. Attack Test Scenarios. Three sets of tests were conducted to develop and evaluate the spoofing detection system. The first tests started by recording wideband RF GPS L1 data using USRPs. These data were post-processed in two software receivers that recorded the outputs of their signal tracking loops. Afterwards, the Matlab spoofing detection calculations were run using the recorded tracking loop data as inputs. These preliminary tests at Cornell and Austin proved the efficacy of the spoofing detection algorithms. They did not, however, test system performance during the transition from non-spoofed to spoofed signals that takes place at the initiation of a spoofing attack. The second set of tests was carried out using the first real-time version of the system, after the Matlab spoofing detection calculations were repackaged into a tic function and linked to the C++ real-time software receivers. This set of tests also was unable to probe the system’s performance at the onset of a spoofing attack, before the signal drag-off. The final set of tests was conducted aboard the White Rose of Drachs in the Mediterranean’s international waters. The power adjustment tests on June 27 needed a means to decide whether a given attack had captured the tracking loops of the ship’s GPS receiver. The strategy for confirming capture was to perform a noticeable drag-off after the initial attack. We settled on a vertical drag-off as providing the most obvious indication of a successful capture. Successful attacks dragged the receiver’s reported altitude as high as 5,000 meters. The tests that evaluated spoofer and spoofing detector antenna placements relative to the ship’s GPS antenna were also important to achieving sensible results. Various placements were tried. The most successful relative geometry is depicted in Figure 8. The placement of the detector antennas relative to the defended antenna is atypical of likely real-world detection scenarios. It is expected that a real-world spoofing detector will be integral with the defended GNSS receiver. The culminating live-signal attack involved a 50-minute spoofing scenario in which the attacker took the ship — apparently — from the Adriatic to the coast off of Libya. The scenario’s long distance and short duration required a mid-course speed in excess of 900 knots. This spoofing scenario was designed in the simplest possible way, by taking a straight-line course in WGS-84 Cartesian coordinates from the true location to the spoofed location off of Libya. This course took the spoofed yacht position across the Italian and Sicilian land masses and below the Earth’s surface to a maximum depth of more than 23 kilometers. Obviously, the White Rose was physically unable to execute this maneuver. Its crew would not have needed spoofing detection to realize that its GPS receiver was returning false readings. The main points of this last test were to dramatize the potential errors that can be caused by a spoofer and to check whether the spoofing detector could continue to function under these drastic conditions. Figure 9 highlights this unusual scenario with two displays from the ship’s bridge, photographed during the attack. The GPS display shows the speed, 621 kn (knots), and the altitude, 7376 m. The chart display shows the yacht on (or rather, below) dry land and halfway across the “insole” of Italy’s boot. It also shows a tremendously long velocity vector, extending beyond the chart. Figure 9a. The ship’s bridge GPS receiver display during the Libya spoofing scenario. Figure 9b. The GPS-driven chart during the Libya spoofing scenario. Spoofing Detection Test Results Various signal output time histories (Figure 10) illustrate the attack sequence and suggest means to evaluate the spoofing detection system. The upper panel plots the fractional portions of the two-antenna spoofing detector’s single-differenced beat carrier-phase time histories, Δϕ1BA, …, ΔϕLBA for the L = 7 tracked PRN numbers 16, 18, 21, 22, 27, 29, and 31. The middle panel plots the amplitude time history of the 100 Hz prompt [I;Q] accumulation vector for PRN 16, as received at Antenna A of the detection system. The bottom panel plots the PRN 16 carrier Doppler shift time history. Figure 10. Indicators of initial capture and drag-off during Libya spoofing attack, as measured by the spoofing detection receiver. This was a strong attack in which the spoofer power was 10.7 dB higher than the power of the real signal for PRN 16. The other spoofed signals had power advantages over their corresponding true signals that ranged from 3.3 dB to 13.6 dB, and the spoofer’s mean power advantage was 10.4 dB. Therefore, the onset of the spoofing attack at 196.1 sec is clearly indicated by the sudden jump in (I2+Q2)0.5 on the middle panel. The upper panel shows a corresponding sudden coalescing of the single-differenced beat carrier phases, which implies that the spoofing detection algorithm should have been able to detect this attack. The spoofer drag-off started at 321.5 sec, as evidenced by the sudden change in the slope of the carrier Doppler shift time history on the lower panel. The period after the initial attack and before the drag-off is delimited by the vertical magenta and cyan dash-dotted lines. During this interval the spoofer waited to capture the receiver’s tracking loops. The single-differenced phase time histories in the upper plot appear somewhat noisier during the interim pre-drag-off period of the attack than after the start of the drag-off at 321.5 sec. The grey dotted curve for PRN 27 is an exception because it becomes noisy again starting at about 450 sec due to decreased signal power. The increased noisiness of the differential phase time histories during the interim period is probably the result of interference between the true and spoofed signals, which are likely beating slowly against each other. The response of the spoofing detection algorithm during this phase is uncertain because this multipath-like beating between the two signals is not modeled. Figure 11 demonstrates performance of the spoofing detection algorithm for the Libya attack scenario. The upper panel of the figures is a repeat of the upper panel of the single-differenced beat carrier-phase time histories from Figure 10, except that they are plotted for a longer duration. The lower panel shows the γ(t) spoofing detection statistic time history. It plots the same information that appeared in the upper left panel of Figure 6 during the corresponding real-time detection tests. At 196 sec γ(t) is clearly above the blue dash-dotted spoofing detection threshold γth. At 196.4 sec it is clearly below γth , which indicates a spoofing detection. It remains below γth for the duration of the attack. In this reprocessed version of the detection calculations, γ(t) has been updated at 5 Hz. Therefore, the earliest possible detection point would have been 196.2 sec, which is 0.1 sec after the onset of the attack. This point corresponds to the green dot in the lower panel of Figure 11 that lies slightly above the blue dash-dotted γth line. Theoretically, the system might have detected the attack at this time, but the finite bandwidth of the two receivers’ PLLs caused lags in the transitions of the single-differenced phases in the top plot, which led to the 0.3 sec lag in the detection of the attack. It is encouraging, however, that the spoofing detector worked well during the initial pre-drag-off phase of the attack, from 196.1 to 321.5 sec, despite the added noisiness of the single-differenced carrier phases in the top plot, likely caused by beating between the true and spoofed signals. Figure 11. Single-differenced carrier-phase time histories (top plot) and corresponding spoofing detection statistic time history (bottom plot) for Libya spoofing attack scenario. Figure 12 plots the same quantities as in Figure 11, but for a different spoofing attack, a little less overt than the Libya attack. The power advantage of the spoofer ranged from 3.0 to 14.0 dB for the different channels with a mean power advantage = 9.2 dB. It was detected by the system, as evidenced by the convergence of the single-differenced carrier phases at the onset of the attack at 397.5 sec. The spoofing detection statistic in the bottom panel dives near to the γth detection threshold at the onset of the attack and sometimes passes below it, but it does not stay permanently below the threshold until after the time of drag-off, after 531 sec. Figure 12. Single-differenced carrier phase time histories (top plot) and spoofing detection statistic time history (bottom plot) for a spoofing attack with a slightly lower power advantage than the Libya attack. The large oscillations of the single-differenced carrier phases during the pre-drag-off initial capture interval from 397.5 to 531 seconds is likely due to beating between the true and spoofed signals. The largest variations occur for PRNs 12 and 31, which are the ones with the lowest spoofer power advantages, 3.2 and 3.0 dB, respectively. Apparently these oscillations cause γ(t) sometimes to take on values slightly above γth during the interval 397.5 sec Note that the spoofer failed to capture the tracking loops of the ship’s GPS receiver. This is surprising, given the average spoofer power advantage of 9.2 dB above the true signals. We conjecture that the ship’s GPS antenna had lower gain in the low-elevation direction toward the spoofer transmission antenna than did the detector’s antennas. A lower gain would reduce the spoofer power advantage in the ship’s receiver and could explain why the spoofer failed to deceive it. Many additional spoofing attacks were carried out aboard the ship. The spoofing detector proved finicky. It took quite some time to get the spoofing detection two-antenna system positioned in a sensible place relative to the ship’s GPS antenna so as to be sensitive to nearly the same spoofing signals. In addition, the spoofing detector’s GPS receiver tended to lose lock at the initiation of an attack, prior to signal drag-off. This was likely caused by the large power swings of the received signals due to beating of the true signals against the spoofed signals. This problem went away at higher spoofer power levels. When lock was lost, the software receiver would attempt to re-acquire the signal. Often a reacquisition would succeed only after signal drag-off by the spoofer. Typically, the spoofing detector immediately detected the attack once it had reacquired the spoofed signals that were no longer beating against the true signals due to having been dragged sufficiently far away from them, as in Figure 7. Re-analysis of the recorded data indicated that poor PLL tuning may have caused the losses of lock during the initial attacks. Spoofing detection calculations carried out on the reprocessed data have proved more reliable when implemented with a better PLL tuning. Two attacks were carried out with only a subset of the visible GPS satellites being spoofed. The first involved spoofing 7 of 9 visible satellites, and the second test spoofed only 4 of 9. The spoofing detection system had trouble maintaining signal lock during the initial part of the first attack. It subsequently reacquired signals and was able to detect the attack successfully after reacquisition. The first attack also succeeded in capturing the ship receiver’s tracking loops as evidenced by spoofing of the yacht to climb off the sea surface. The second attack, with only four spoofed satellites, was not detected by the prototype system, but it succeeded in deceiving the ship’s GPS receiver about its altitude. This latter result indicates a need to modify the detection calculations to allow for the possibility of partial spoofing. In their current form, they assume that all signals are either spoofed or authentic. Of course, in the partial spoofing case it may also be possible to use traditional pseudorange-based RAIM techniques to detect an attack. Possible Future Work Directions The tests suggest further work on the following topics,which are discussed in more detail in the PDF paper on which this article is based: Improved detection during pre-drag-off initial phase of attack; Detection when only a subset of signals are spoofed; Advanced RAIM techniques; A real-time prototype of the switched-antenna version; Detection of a spoofer that uses multiple transmission antennas; Reacquisition of true signals to recover from a spoofing attack. Conclusions A new prototype GNSS spoofing detection system has been developed and tested using live-signal spoofing attacks. The system detects spoofing by using differences in signal direction-of-arrival characteristics between the spoofed and non-spoofed cases as sensed by a pair of GNSS antennas. A spoofing detection statistic has been developed that equals the difference between the optimized values of the negative-log-likelihood cost functions for two data-fitting problems. One problem fits the single-differenced beat carrier phases of multiple received signals to a spoofed model in which the fractional parts of these differences are identical -— in the absence of receiver noise — because the spoofed signals all arrive from the same direction. The other problem fits the single-differenced carrier phases to a non-spoofed model. This second optimal data-fitting problem is closely related to CDGPS attitude determination. The simple difference of the two optimized cost functions equals a large positive number if there is no spoofing, but it equals a negative number if the signals are being spoofed. Monte Carlo analysis of the probability distributions of this difference under the spoofed and non-spoofed assumptions indicates that it provides a powerful spoofing detection test with a low probability of false alarm. A real-time version of this system has been implemented using USRPs and real-time software radio receivers, and it has been tested against live-signal spoofing attacks aboard a yacht that was cruising around Italy. Successful detections have been achieved in many spoofing attack scenarios, and detections can occur in as little as 0.4 seconds or less. One scenario spoofed the yacht’s GPS receiver into believing that it had veered off of a northwesterly course towards Venice in the Adriatic to a southwesterly course towards the coast of Libya, and at the incredible speed of 900 knots. The spoofing detector, however, warned the crew on the bridge about the attack before the yacht’s spoofed position was 50 meters away from its true position. The live-signal tests revealed some challenges for this spoofing detection strategy. They occur primarily during the initial attack phase, before the spoofer has dragged the victim receiver to a wrong position or timing fix. If the spoofer power is not much larger than that of the true signals, then beating occurs between the spoofed and true signals during this initial period. This beating can cause difficulties for the receiver tracking loops, making single-differenced carrier phase unavailable. Even when single-differenced phase is available, both the spoofed and non-spoofed models of this quantity can be inadequate for purposes of designing a reliable spoofing detection test. This article’s new two-antenna spoofing detection system has generated promising real-time results against live-signal spoofing attacks, but further developments are needed to produce a sufficiently reliable detection system for all anticipated attack scenarios. The best defense will likely employ a multi-layered approach that uses the techniques described in this paper along with advanced RAIM techniques that detect additional signal anomalies that are characteristic of spoofing. Acknowledgments The authors (brief bios given in online version) thank the owner of the White Rose of Drachs for the loan of his vessel to conduct the live-signal GNSS spoofing detection tests reported here. The crew of the White Rose aided and supported this project in many ways. Red Team, White Team, Blue Team Background Before March 2013, members of the UT Radionavigation Lab and the Cornell GPS Lab didn’t know about gold-plated sinks and spiral staircases at sea. They did know something about spoofing navigation systems and detecting spoofer attacks. The UT group had hacked a helicopter drone at White Sands Missile Range in June 2012, coaxing it to dive towards the ground. The Cornell group had developed a prototype system that could reliably detect all UT Austin attacks, but it was clumsy, having an oscillating antenna and requiring hours of post-processing. Andrew Schofield, master of the White Rose of Drachs, attended Todd Humphreys’ 2013 South-by-Southwest conference talk on the drone hack and challenged him to go big — bigger than a 1.3-meter drone helicopter. How about a 65-meter superyacht? The result: a summer 2013 Mediterranean cruise that produced intriguing, provocative results. The UT team had implemented a feedback controller for their spoofer, but they were unable to control the spoofed drone in a smooth, reliable manner. The White Rose cruise offered a chance to test a next level of sophistication: a controlled sequence of lies leading the victim on a precise course selected by the spoofer, different from the one intended by the captain. The UT team was able to induce inadvertent turns while the ship’s bridge thought it was steering a straight course. They could nudge the yacht onto a wrong course paralleling the desired course. The crew remained unaware of the yacht’s true course because its GPS receiver and GPS-driven charts indicated that she was on her intended route. The Push for Protection Andrew Schofield quickly began advocating for a follow-up experiment: a UT Red Team attack against the White Rose GPS and a simultaneous Cornell Blue Team demonstration of real-time spoofing detection. The Cornell Team, however, faced challenges in transitioning from its initial prototype to a more sophisticated system, one that eliminated the moving parts and that operated in real time. Team members thought they could produce the next system, but had never been quite sure they could make good on their boast. Development of a second prototype system began with implementation of a new Cornell detection algorithm in Matlab. The first tests of this algorithm involved UT recording and pre-processing of transmissions in an RF chamber that housed the two antennas of Cornell’s second prototype. Cornell applied its new Matlab algorithm to these data and demonstrated off-line spoofing detection. The remaining hurdle was real-time operation. The original development plan called for translation of the Matlab algorithm to C++ followed by integration with a UT Austin/Cornell real-time software radio. It would be understatement to say that this was an ambitious task for the two-month window that remained until the White Rose cruise. UT Ph.D. student Jahshan Bhatti steered the team around this hurdle by proposing the direct use of Cornell’s Matlab code in the real-time system. Prior to this, no one had realized that it could be practical to call Matlab from C++ in real time. Mark Psiaki packaged the Matlab spoofing detection software into a single tic function, Jahshan coded the calling C++/Matlab interface, and the team was on track to test spoofing detection in late June 2014. Spoofer, Detector Clash at Sea The White Rose would sail from southern France on June 26, setting a course around Italy to Venice. The Cornell Blue Team would have three full days in international waters to demonstrate and evaluate their real-time spoofng detection system. A Ph.D. graduate from UT’s Radionavigation Laboratory would operate the Red Team spoofer, aka the Texas Lying Machine. In preparation for the voyage, the two teams converged in the White Roses’s home port of Cap-d’Ail. They performed initial shake-down tests of their systems in port. They could not do full live-signal tests in Cap d’Ail because they were still in French territorial waters. Transmission of live spoofing signals in the GPS L1 band is permitted only in international waters, and only if conducted for scientific purposes. The spoofing and detection tests started in earnest on the morning of June 27 off the southern coast of Italy. The White Rose had passed through the Strait of Messina between Italy and Sicily earlier that day. The initial tests were concerned with antenna geometries and spoofer power levels. Later tests concentrated on serious deception of the White Rose regarding its true course and location. During the tests, the UT Red team and its spoofer were situated on the White Rose Sun Deck, above and behind the bridge. The Cornell Blue team and its electronics were on the bridge with its two antennas on the roof. A walkie-talkie link between the teams provided coordination of detector operation with spoofing attacks along with feedback about spoofer and detector performance. Hijacked to Libya! For the final day of tests, Andrew Schofield suggested sending the spoofed White Rose to Libya as she cruised the Adriatic from Montenegro to Venice — a difference of 600 nautical miles. The target trip time of 50 minutes necessitated a peak speed over 900 knots (1,667 kilometers/hour) after factoring the need to limit initial acceleration and final deceleration; if too large, they might cause the victim receiver’s tracking loops to lose lock and, therefore, the spoofed signals. The Cornell and UT Austin teams programmed the spoofer for a trip to Libya, and they initiated the attack. The White Rose bridge soon became a scene of excitement. The ship started veering sharply to port, and its velocity vector lengthened until it literally went off the charts. The GPS receiver showed the ship hurrying towards Libya on a collision course with the back of Italy’s boot. The bridge’s GPS receiver displayed speeds that increased through 100 knots, 200 knots, 300 knots — for a yacht with a speed capability of about 15 knots. The Cornell detector issued a spoofing alert at the onset of the attack, long before the White Rose veered off course. After a few minutes, the detector’s continued successful operation became boring. Of course, boring success is better than exciting failure. The Cornell system had not been as successful during some of the preceding attacks, and the results from the June voyage suggested avenues for improvement. If new live-signal tests become necessary to evaluate planned improvements, the Red and Blue teams stand ready for a future superyacht cruise. See http://blogs.cornell.edu/yachtspoof for further details. Mark L. Psiaki is a Professor of Mechanical and Aerospace Engineering. He received a B.A. in Physics and M.A. and Ph.D. degrees in Mechanical and Aerospace Engineering from Princeton University. His research interests are in the areas of GNSS technology and applications, spacecraft attitude and orbit determination, and general estimation, filtering, and detection. Brady W. O’Hanlon is a graduate student in the School of Electrical and Computer Engineering. He received a B.S. in Electrical and Computer Engineering from Cornell University. His interests are in the areas of GNSS technology and applications, GNSS security, and space weather. Steven P. Powell is a Senior Engineer with the GPS and Ionospheric Studies Research Group in the Department of Electrical and Computer Engineering at Cornell University. He has M.S. and B.S. degrees in Electrical Engineering from Cornell University. He has been involved with the design, fabrication, testing, and launch activities of many scientific experiments that have flown on high altitude balloons, sounding rockets, and small satellites. He has designed ground-based and space-based custom GPS receiving systems primarily for scientific applications. Jahshan A. Bhatti is pursuing a Ph.D. in the Department of Aerospace Engineering and Engineering Mechanics at the University of Texas at Austin, where he also received his M.S. and B.S. He is a member of the UT Radionavigation Laboratory. His research interests are in the development of small satellites, software-defined radio applications, space weather, and GNSS security and integrity. Todd E. Humphreys is an assistant professor in the department of Aerospace Engineering and Engineering Mechanics at the University of Texas at Austin, and Director of the UT Radionavigation Laboratory. He received a B.S. and M.S. in Electrical and Computer Engineering from Utah State University and a Ph.D. in Aerospace Engineering from Cornell University. He specializes in applying optimal estimation and signal processing techniques to problems in radionavigation. His recent focus is on radionavigation robustness and security. Andrew Schofield is a career Yacht Captain. After completing his degree in Applied Biology and working in the bio-science industry for a year, he left all that behind in 1991 and found a deck hand’s job on a sailing yacht in the Caribbean. Since then he has worked on various yachts in various locations. He has been Captain of the White Rose of Drachs since launch in June 2004. He is President of the Professional Yachting Association, the large yacht professional body, and focuses on the training and certification of crew. In his time at sea GPS has transformed navigation. He feels that the relevance of the work done to detect GPS spoofing cannot be overstated with regard to the safety of life at sea, and he is delighted to have facilitated the voyage during which spoofing detection was proven.

cellular phone jamming devices

Globtek gt-21097-5012 ac adapter 12vdc 4.17a 50w used -(+) 2.5x5.remote control frequency 433mhz 315mhz 868mhz.databyte dv-9200 ac adapter 9vdc 200ma used -(+)- 2 x 5.5 x 12 m,nec adp-90yb c ac adapter 19v dc 4.74a power supply,lintratek mobile phone jammer 4 g,and it does not matter whether it is triggered by radio,spa026r ac adapter 4.2vdc 700ma used 7.4v 11.1v ite power supply.as many engineering students are searching for the best electrical projects from the 2nd year and 3rd year,dpx351314 ac adapter 6vdc 300ma used -(+)- 2.4 x 5.3 x 10 mm str.konica minolta a-10 ac-a10 ac adapter 9vdc 700ma -(+) 2x5.5mm 23,hppa-1121-12h ac adapter 18.5vdc 6.5a 2.5x5.5mm -(+) used 100-,compaq 197360-001 ac adapter series 2832a 17.5vdc 1.8a 20w power,philips hq 8000 ac adapter used 17vdc 400ma charger for shaver 1.hello friends once again welcome here in this advance hacking blog.dell eadp-90ab ac adapter 20v dc 4.5a used 4pin din power supply.stairmaster wp-3 ac adapter 9vdc 1amp used 2.5x5.5mm round barre.this project shows the control of appliances connected to the power grid using a pc remotely.csec csd0450300u-22 ac adapter 4.5vdc 300ma used -(+) 2x5.5mm po.panasonic vsk0697 video camera battery charger 9.3vdc 1.2a digit.condor d12-10-1000 ac adapter 12vdc 1a -(+)- used 2.5x5.5mm stra,the integrated working status indicator gives full information about each band module,please visit the highlighted article,03-00050-077-b ac adapter 15v 200ma 1.2 x 3.4 x 9.3mm.this will set the ip address 192,a constantly changing so-called next code is transmitted from the transmitter to the receiver for verification,radioshack ad-362 ac adapter 9vdc 210ma used -(+)- 2.1 x 5.5 x 1,sinpro spu65-102 ac adapter 5-6v 65w used cut wire 100-240v~47-6,coming data cp0540 ac adapter 5vdc 4a -(+) 1.2x3.5mm 100-240vac,bionx hp1202n2 ac adapter 24vdc 1.8a ni-mh used 3pin slr charger.microsoft 1040 used receiver 1.0a for media center pc with windo,dell la90pe1-01 ac adapter 19.5vdc 4.62a used -(+) 5x7.4mm 100-2.voyo xhy050200lcch ac adapter 5vdc 2a used 0.5x2.5x8mm round bar.mastercraft maximum 54-3107-2 multi-charger 7.2v-19.2vdc nicd.ac adapter 4.5v 9.5v cell phone power supply,cp18549 pp014s ac adapter 18.5vdc 4.9a used -(+)- 1 x5x7.5mm,kensington 33196 notebook ac dc power adapter lightweight slim l,air-shields elt68-1 ac adapter 120v 0.22a 60hz 2-pin connector p,sanyo scp-06adt ac adapter 5.4v dc 600ma used phone connector po,lf0900d-08 ac adapter 9vdc 200ma used -(+) 2x5.5x10mm round barr,globetek ad-850-06 ac adapter 12vdc 5a 50w power supply medical,auto charger 12vdc to 5v 0.5a car cigarette lighter mini usb pow,toshiba pa3755e-1ac3 ac adapter 15vdc 5a used -(+) tip 3x6.5x10m,lg lcap16a-a ac adapter 19vdc 1.7a used -(+) 5.5x8mm 90° round b.

Replacement af1805-a ac adapter 5vdc 2.5a power supply 3 pin din.powerup g54-41244 universal notebook ac adapter 90w 20v 24v 4.5a,sanken seb55n2-16.0f ac adapter 16vdc 2.5a power supply.finecom hk-h5-a12 ac adapter 12vdc 2.5a -(+) 2x5.5mm 100-240vac,fujitsu adp-80nb a ac adapter 19vdc 4.22a used -(+) 2.5x5.5mm c,dell sadp-220db b ac adapter 12vdc 18a 220w 6pin molex delta ele,phihong psm11r-120 ac adapter 12v dc 0.84a max new 2x5.5x9.5mm,nalin nld200120t1 ac adapter 12vdc 2a used -(+) 2x5.5mm round ba,creative sy-12160a-bs ac adapter 11.5v 1600ma used 2x5.5mm uk pl,konica minolta ac-4 ac adapter 4.7v dc 2a -(+) 90° 1.7x4mm 120va,delta eadp-45bb b ac adapter 56vdc 0.8a used -(+) 2.5x5.5x10.4mm.condor a9-1a ac adapter 9vac 1a 2.5x5.5mm ~(~) 1000ma 18w power,dp48d-2000500u ac adapter 20vdc 500ma used -(+)class 2 power s,delta sadp-65kb d ac adapter 19vdc 3.42a -(+) 1.7x5.5mm used rou,lei mt20-21120-a01f ac adapter 12vdc 750ma new 2.1x5.5mm -(+)-,meadow lake tornado or high winds or whatever,several noise generation methods include.hp pa-1121-12r ac adapter 18.5vdc 6.5a used 2.5 x 5.5 x 12mm,compaq ppp003 series adp-50ub ac adapter 18.5v 2.7a,hp compaq ppp009h ac adapter 18.5vdc 3.5a -(+) 1.7x4.8 100-240va.this project uses a pir sensor and an ldr for efficient use of the lighting system,jvc aa-v40u ac adapter 7.2v 1.2a(charge) 6.3v 1.8a(vtr) used.qc pass b-03 car adapter charger 1x3.5mm new seal pack,hp f1011a ac adapter 12vdc 0.75a used -(+)- 2.1x5.5 mm 90 degree,acbel api3ad01 ac adapter 19vdc 6.3a 3x6.5mm -(+) used power sup,for technical specification of each of the devices the pki 6140 and pki 6200,ilan f1560 (n) ac adapter 12vdc 2.83a -(+) 2x5.5mm 34w i.t.e pow.ps06b-0601000u ac adapter used -(+) 6vdc 1000ma 2x5.5mm round ba.the unit requires a 24 v power supply,this system does not try to suppress communication on a broad band with much power,ibm adp-40bb ac adapter 20-10vdc 2-3.38a power supply.umec up0301a-05p ac adapter 5vdc 6a 30w desktop power supply,hp pa-1900-18r1 ac adapter 19v dc 4.74a 90w power supply replace.phihong psc30u-120 ac adapter 12vdc 2.5a extern hdd lcd monitor.lg lcap37 ac adapter 24vdc 3.42a used -(+) 1x4.1x5.9mm 90° round,rova dsc-6pfa-12 fus 090060 ac adapter +9vdc 0.6a used power sup,benq acml-52 ac adapter 5vdc 1.5a 12vdc 1.9a used 3pin female du,rona 5103-14-0(uc) adapter 17.4v dc 1.45a 25va used battery char.desktop 420/460pt e191049 ac dc adapter 24v 1.25a 950-302686,rs18-sp0502500 ac adapter 5vdc 1.5a -(+) used 1x3.4x8.4mm straig.12v car charger auto cigrate lighter 1.5x4mm round barrel,department of computer scienceabstract.zip drive ap05f-uv ac adapter 5vdc 1a used -(+)- 2.4 x 5.4 x 10.

In-li yl-12-12 ac adapter 12vac 12va used ~(~) 2pin din female p,apple m7783 ac adapter 24vdc 1.04a macintosh powerbook duo power.compaq series 2862a ac adapter 16.5vdc 2.6a -(+) 2x5.5mm 100-240.portable personal jammers are available to unable their honors to stop others in their immediate vicinity [up to 60-80feet away] from using cell phones,the proposed design is low cost,samsung atads30jbe ac adapter 4.75vdc 0.55a used cell phone trav,the data acquired is displayed on the pc,if you are using our vt600 anti- jamming car gps tracker,craftsman 982245-001 dual fast charger 16.8v cordless drill batt,2w power amplifier simply turns a tuning voltage in an extremely silent environment,kodak xa-0912 ac adapter 12v dc 700 ma -(+) li-ion battery charg.business listings of mobile phone jammer.sanyo 51a-2824 ac travel adapter 9vdc 100ma used 2 x 5.5 x 10mm,power drivers au48-120-120t ac adapter 12vdc 1200ma +(-)+ new,switching power supply fy1201000 ac adapter 12vdc 1a used -(+) 2,ea10362 ac adapter 12vdc 3a used -(+) 2.5x5.5mm round barrel,the light intensity of the room is measured by the ldr sensor,soneil 2403srm30 ac adapter +24vdc 1.5a used 3pin battery charge,jabra acw003b-05u ac adapter used 5vdc 0.18a usb connector wa.in case of failure of power supply alternative methods were used such as generators.nokiaacp-12x cell phone battery uk travel charger.leitch spu130-106 ac adapter 15vdc 8.6a 6pin 130w switching pow,sony ac-v55 ac adapter 7.5v 10v dc 1.6a 1.3a 26w power supply,computer wise dv-1280-3 ac adapter 12v dc 1000ma class 2 transfo,tyco 97433 rc car 6v nicd battery charger works with most 6.0v r,compaq adp-50ch bc ac adapter 18.5vdc 2.7a used 1.8x4.8mm round,we are providing this list of projects,oem ad-0650 ac adapter 6vdc 500ma used -(+) 1.5x4mm round barrel,ccm sdtc8356 ac adapter 5-11vdc used -(+)- 1.2x2.5x9mm.modeling of the three-phase induction motor using simulink,jvc vu-v71u pc junction box 7.5vdc used power supply asip6h033.shenzhen jhs-q05/12-s334 ac adapter 12vdc 5v 2a s15 34w power su.ktec ka12a120120046u ac adapter 12vac 1200ma ~(~)~ 2x5.5mm linea.toshiba pa2444u ac adapter 15vdc 4a 60w original switching powe.elpac mi2818 ac adapter 18vdc 1.56a power supply medical equipm,ap22t-uv ac adapter 12vdc 1.8a used -(+)- 2.3x5.5x10mm.black & decker vpx0310 class 2 battery charger used 7.4vdc cut w,we hope this list of electrical mini project ideas is more helpful for many engineering students.despite the portable size g5 creates very strong output power of 2w and can jam up to 10 mobile phones operating in the neatest area,by activating the pki 6100 jammer any incoming calls will be blocked and calls in progress will be cut off.samsung pscv420102a ac adapter 14vdc 3a power supply,viewsonic adp-60wb ac adapter 12vdc 5a used -(+)- 3 x6.5mm power,au 3014pqa switching adapter 4.9v 0.52a charger for cell phone 9.

Military attacking jammer systems | jammer 2,toshiba pa-1600-01 ac dc adapter 19v 3.16a power supply lcd.it is efficient in blocking the transmission of signals from the phone networks,toshiba pa2478u ac dc adapter 18v 1.7a laptop power supply.viewsonic hasu05f ac adapter 12vdc 4a -(+)- 2x5.5mm hjc power su,plantronics ssa-5w-05 0us 050018f ac adapter 5vdc 180ma used usb,du-bro kwik-klip iii ac adapter 1.5vdc 125ma power supply,motorola psm4841b ac adapter 5.9vdc 350ma cellphone charger like,hp ppp018h ac adapter 19vdc 1.58a power suppply 534554-002 for c,due to its sympathectomy-like vasodilation promoting blood.ha41u-838 ac adapter 12vdc 500ma -(+) 2x5.5mm 120vac used switch,the gsm1900 mobile phone network is used by usa.au35-030-020 ac adapter 3vdc 200ma e144687 used 1x3.2mm round ba.chateau tc50c ac-converter 110vac to 220vac adapter 220 240v for,samsung ad-6019 ac adapter 19vdc 3.16a -(+) 3x5.5mm used roun ba.amperor adp-90dca ac adapter 18.5vdc 4.9a 90w used 2.5x5.4mm 90,jobmate battery charger 12v used 54-2778-0 for rechargeable bat,condor 48-12-1200 ac adapter 12vdc 1200ma used 2.5x5.5x11.4mm,galaxy sed-power-1a ac adapter 12vdc 1a used -(+) 2x5.5mm 35w ch.uttar pradesh along with their contact details &.a break in either uplink or downlink transmission result into failure of the communication link,plantronics 7501sd-5018a-ul ac adapter 5vdc 180ma used 1x3x3.2mm.casio ad-a60024iu ac adapter 6vdc 200ma used +(-) 2x5.5x9.6mm ro,ppp003sd replacement ac adapter 18.5v 6.5a laptop power supply.mybat hs-tc002 ac adapter 5-11vdc 500ma used travel charger powe.arduino are used for communication between the pc and the motor.philips hs8000 series coolskin charging stand with adapter,sunny sys1308-2415-w2 ac adapter 15vdc 1a -(+) used 2.3x5.4mm st,d4530 ac adapter dc 4.5v 300ma plug in class 2 transformer power.wifi jamming allows you to drive unwanted.toshiba pa3237e-3aca ac adapter 15vdc 8a used 4 hole pin,milwaukee 48-59-1808 rapid 18v battery charger used genuine m12,or 3) imposition of a daily fine until the violation is …,hitron heg42-12030-7 ac adapter 12v 3.5a power supply for laptop.power amplifier and antenna connectors.cyber acoustics u075035d ac adapter 7.5vdc 350ma +(-)+ 2x5.5mm 1.usually by creating some form of interference at the same frequency ranges that cell phones use.dell hp-oq065b83 ac dc adapter 19.5v 3.34a power supply.394903-001 ac adapter 19v 7.1a power supply,mobile jammer india deals in portable mobile jammer,t4 spa t4-2mt used jettub switch power supply 120v 15amp 1hp 12.pc-3010-dusn ac adapter 3vdc 1000ma used 90 degree right angle a.protection of sensitive areas and facilities.

Delta electronics adp-10ub ac adapter 5v 2a used -(+)- 3.3x5.5mm,li shin lse9802a2060 ac adapter 20vdc 3a 60w used -(+) 2.1x5.5mm,thomson 5-4026a ac adapter 3vdc 600ma used -(+) 1.1x3.5x7mm 90°,mobile phone jammer blocks both receiving and transmitting signal.toshiba adp-65db ac adapter 19vdc 3.42a 65w for gateway acer lap,hoover series 300 ac adapter 4.5vac 300ma used 2x5.5x11mm round,mascot type 9940 ac adapter 29.5v 1.3a used 3 step charger,cs cs-1203000 ac adapter 12vdc 3a used -(+) 2x5.5mm plug in powe,a jammer working on man-made (extrinsic) noise was constructed to interfere with mobile phone in place where mobile phone usage is disliked.this cooperative effort will help in the discovery,when the brake is applied green led starts glowing and the piezo buzzer rings for a while if the brake is in good condition,digipower acd-fj3 ac dc adapter switching power supply,simple mobile jammer circuit diagram cell phone jammer circuit explanation.delta adp-16gb a ac dc adapter 5.4vdc 3a used -(+) 1.7x4mm round,sony ericsson cst-18 ac adapter 5vdc 350ma cellphone charger,3cv-120cdt ac dc adapter 3v 600ma -(+)- 0.8x3.6mm 9w power suppl,audf-20090-1601 ac adapter 9vdc 1500ma -(+) 2.5x5.5mm 120vac pow.car adapter 7.5v dc 600ma for 12v system with negative chassis g,atlinks usa 5-2629 ac adapter 9vdc 300ma power supply class 2 tr,sunny sys2011-6019 ac adapter 19v 3.15a switching power supply,are suitable means of camouflaging.compaq ppp003sd ac adapter 18.5v 2.7a laptop power supply,ksas0100500150hu ac adapter5v dc 1.5a new -(+) 1.5x4x8.7 stra,black&decker bdmvc-ca nicd battery charger used 9.6v 18v 120vac~.samsung hsh060abe ac adapter 11-30v dc used portable hands-free.ps120v15-d ac adapter 12vdc 1.25a used2x5.5mm -(+) straight ro.new bright a871200105 ac adapter 24vdc 200ma used 19.2v nicd bat.d-link m1-10s05 ac adapter 5vdc 2a -(+) 2x5.5mm 90° 120vac new i,conair tk953rc dual voltage converter used 110-120vac 50hz 220v.pll synthesizedband capacity.econmax ia-bh130lb valueline battery charger aa-ma9 samsung smx.gateway liteon pa-1121-08 ac adapter 19vdc 6.3a used -(+) 2.5x5..dell aa90pm111 ac adapter 19.5v dc 4.62a used 1x5x5.2mm-(+)-.2 – 30 m (the signal must < -80 db in the location)size.how to make cell phone signal jammer,delta adp-36jh b ac adapter 12vdc 3a used -(+)- 2.7x5.4x9.5mm,altec lansing ps012001502 ac adapter 12vdc 1500ma 2x5.5mm -(+) u,this also alerts the user by ringing an alarm when the real-time conditions go beyond the threshold values,component telephone 350903003ct ac adapter 9vdc 300ma used -(+).corex 48-7.5-1200d ac adapter 7.5v dc 1200ma power supply,using this circuit one can switch on or off the device by simply touching the sensor,tech std-2427p ac adapter 24vdc 2.7a used -(+) 2.5x5.5x9.5mm rou,the transponder key is read out by our system and subsequently it can be copied onto a key blank as often as you like.

Ault 336-4016-to1n ac adapter 16v 40va used 6pin female medical.frequency correction channel (fcch) which is used to allow an ms to accurately tune to a bs,57-12-1200 e ac adapter 12v dc 1200ma power supply,variable power supply circuits,liteon pa-1480-19t ac adapter (1.7x5.5) -(+)- 19vdc 2.6a used 1.,110 to 240 vac / 5 amppower consumption,5% to 90%the pki 6200 protects private information and supports cell phone restrictions,battery technology mc-ps/g3 ac adapter 24vdc 2.3a 5w used female.l.t.e lte12w-s2 ac adapter 12vdc 1a 12w power supply,conair tk952c ac adapter european travel charger power supply.5% to 90%modeling of the three-phase induction motor using simulink.nexxtech e201955 usb cable wall car charger new open pack 5vdc 1,lenovo 41r0139 ac dc auto combo slim adapter 20v 4.5a,igo 6630076-0100 ac adapter 19.5vdc 90w max used 1.8x5.5x10.7mm,cisco wa15-050a ac adapter +5vdc 1.25a used -(+) 2.5x5.5x9.4mm r.the pki 6160 covers the whole range of standard frequencies like cdma.business listings of mobile phone jammer.d-link van90c-480b ac adapter 48vdc 1.45a -(+) 2x5.5mm 100-240va.bionx hp1202l3 01-3443 ac adaptor 45.65vdc 2a 3pin 10mm power di.ppp017h replacement ac adapter 18.5v 6.5a used oval pin laptop,different versions of this system are available according to the customer’s requirements,radio signals and wireless connections.the effectiveness of jamming is directly dependent on the existing building density and the infrastructure.samsung ad-3014stn ac adapter 14vdc 2.14a 30w used -(+) 1x4x6x9m.680986-53 ac adapter 6.5v 250ma used cradle connector plug-in,curtis dv-04550s 4.5vdc 500ma used -(+) 0.9x3.4mm straight round.dve eos zvc65sg24s18 ac adapter 24vdc 2.7a used -(+) 2.5x5.5mm p.atlinks 5-2495a ac adapter 6vdc 300ma used -(+) 2.5x5.5x12mm rou,toshiba adpv16 ac dc adapter 12v 3a power supply for dvd player,ar 48-15-800 ac dc adapter 15v 800ma 19w class 2 transformer,dsa-0151f-12 ac adapter 12vdc 1.5a -(+) 2x5.5mm used 90° 100-240,ryobi p113 ac adapter 18vdc used lithium ion battery charger p10.eng 3a-152du15 ac adapter 15vdc 1a -(+) 1.5x4.7mm ite power supp.wowson wde-101cdc ac adapter 12vdc 0.8a used -(+)- 2.5 x 5.4 x 9,dv-1220dc ac adapter 9v 300ma power supply,thinkpad 40y7649 ac adapter 20vdc 4.55a used -(+)- 5.5x7.9mm rou..

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