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Mitigation Through Adaptive Filtering for Machine Automation Applications By Luis Serrano, Don Kim, and Richard B. Langley Multipath is real and omnipresent, a detriment when GPS is used for positioning, navigation, and timing. The authors look at a technique to reduce multipath by using a pair of antennas on a moving vehicle together with a sophisticated mathematical model. This reduces the level of multipath on carrier-phase observations and thereby improves the accuracy of the vehicle’s position. INNOVATION INSIGHTS by Richard Langley “OUT, DAMNED MULTIPATH! OUT, I SAY!” Many a GPS user has wished for their positioning results to be free of the effect of multipath. And unlike Lady Macbeth’s imaginary blood spot, multipath is real and omnipresent. Although it may be considered beneficial when GPS is used as a remote sensing tool, it is a detriment when GPS is used for positioning, navigation, and timing — reducing the achievable accuracy of results. Clearly, the best way to reduce the effects of multipath is to try avoiding it in the first place by siting the receiver’s antenna as low as possible and far away from potential reflectors. But that’s not always feasible. The next best approach is to reduce the level of the multipath signal entering the receiver by attenuating it with a suitably designed antenna. A large metallic ground plane placed beneath an antenna will modify the shape of the antenna’s reception pattern giving it reduced sensitivity to signals arriving at low elevation angles and from below the antenna’s horizon. So-called choke-ring antennas also significantly attenuate multipath signals. And microwave-absorbing materials appropriately placed in an antenna’s vicinity can also be beneficial. Multipath can also be mitigated by special receiver correlator designs. These designs target the effect of multipath on code-phase measurements and the resulting pseudorange observations. Several different proprietary implementations in commercial receivers significantly reduce the level of multipath in the pseudoranges and hence in pseudorange-based position and time estimates. Some degree of multipath attenuation can be had by using the low-noise carrier-phase measurements to smooth the pseudoranges before they are processed. The effect of multipath on carrier phases is much smaller than that on pseudoranges. In fact, it is limited to only one-quarter of the carrier wavelength when the reflected signal’s amplitude is less than that of the direct signal. This means that at the GPS L1 frequency, the multipath contamination in a carrier-phase measurement is at most about 5 centimeters. Nevertheless, this is still unacceptably large for some high-accuracy applications. At a static site, with an unchanging multipath environment, the signal reflection geometry repeats day to day and the effect of multipath can be reduced by sidereal filtering or “stacking” of coordinate or carrier-phase-residual time series. However, this approach is not viable for scenarios where the receiver and antenna are moving such as in machine control applications. Here an alternative approach is needed. In this month’s column, I am joined by two of my UNB colleagues as we look at a technique that uses a pair of antennas on a moving vehicle together with a sophisticated mathematical model, to reduce the level of multipath on carrier-phase observations and thereby improve the accuracy of the vehicle’s position. Real-time-kinematic (RTK) GNSS-based machine automation systems are starting to appear in the construction and mining industries for the guidance of dozers, motor graders, excavators, and scrapers and in precision agriculture for the guidance of tractors and harvesters. Not only is the precise and accurate position of the vehicle needed but its attitude is frequently required as well. Previous work in GNSS-based attitude systems, using short baselines (less than a couple of meters) between three or four antennas, has provided results with high accuracies, most of the time to the sub-degree level in the attitude angles. If the relative position of these multiple antennas can be determined with real-time centimeter-level accuracy using the carrier-phase observables (thus in RTK-mode), the three attitude parameters (the heading, pitch, and roll angles) of the platform can be estimated. However, with only two GNSS antennas it is still possible to determine yaw and pitch angles, which is sufficient for some applications in precision agriculture and construction. Depending on the placement of the antennas on the platform body, the determination of these two angles can be quite robust and efficient. Nevertheless, even a small separation between the antennas results in different and decorrelated phase-multipath errors, which are not removed by simply differencing measurements between the antennas. The mitigation of carrier-phase multipath in real time remains, to a large extent, very limited (unlike the mitigation of code multipath through receiver improvements) and it is commonly considered the major source of error in GNSS-RTK applications. This is due to the very nature of multipath spectra, which depends mainly on the location of the antenna and the characteristics of the reflector(s) in its vicinity. Any change in this binomial (antenna/reflectors), regardless of how small it is, will cause an unknown multipath effect. Using typical choke-ring antennas to reduce multipath is typically not practical (not to mention cost prohibitive) when employing multiple antennas on dynamic platforms. Extended flat ground planes are also impractical. Furthermore, such antenna configurations typically only reduce the effects of low angle reflections and those coming from below the antenna horizon. One promising approach to mitigating the effects of carrier-phase multipath is to filter the raw measurements provided by the receiver. But, unlike the scenario at a fixed site, the multipath and its effects are not repeatable. In machine automation applications, the machinery is expected to perform complex and unpredictable maneuvers; therefore the removal of carrier-phase multipath should rely on smart digital filtering techniques that adapt not only to the background multipath (coming mostly from the machine’s reflecting surfaces), but also to the changing multipath environment along the machine’s path. In this article, we describe how a typical GPS-based machine automation application using a dual-antenna system is used to calibrate, in a first step, and then remove carrier-phase multipath afterwards. The intricate dynamical relationship between the platform’s two “rover” antennas and the changing multipath from nearby reflectors is explored and modeled through several stochastic and dynamical models. These models have been implemented in an extended Kalman filter (EKF). MIMICS Strategy Any change in the relative position between a pair of GNSS antennas most likely will affect, at a small scale, the amplitude and polarization of the reflected signals sensed by the antennas (depending on their spacing). However, the phase will definitely change significantly along the ray trajectories of the plane waves passing through each of the antennas. This can be seen in the equation that describes the single-difference multipath between two close-by antennas (one called the “master” and the other the “slave”):   (1) where the angle  is the relative multipath phase delay between the antennas and a nearby effective reflector (α0 is the multipath signal amplitude in the master and slave antennas, and is dependent on the reflector characteristics, reflection coefficient, and receiver tracking loop). As our study has the objective to mimic as much as possible the multipath effect from effective reflectors in kinematic scenarios with variable dynamics, we decided to name the strategy MIMICS, a slightly contrived abbreviation for “Multipath profile from between receIvers dynaMICS.” The MIMICS algorithm for a dual-antenna system is based on a specular reflector ray-tracing multipath model (see Figure 1). Figure 1. 3D ray-tracing modeling of phase multipath for a GNSS dual-antenna system. 0 designates the “master” antenna; 1, the “slave” antenna; Elev and Az, the elevation angle and the azimuth of the satellite, respectively. The other symbols are explained in the text. After a first step of data synchronization and data-snooping on the data provided by the two receiver antennas, the second step requires the calculation of an approximate position for both antennas, relaxed to a few meters using a standard code solution. A precise estimation of both antennas’ velocity and acceleration (in real time) is carried out using the carrier-phase observable. Not only should the antenna velocity and acceleration estimates be precisely determined (on the order of a few millimeters per second and a few millimeters per second squared, respectively) but they should also be immune to low-frequency multipath signatures. This is important in our approach, as we use the antennas’ multipath-free dynamic information to separate the multipath in the raw data. We will start from the basic equations used to derive the single-difference multipath observables. The observation equation for a single-difference between receivers, using a common external clock (oscillator), is given (in distance units) by:  (2) where m indicates the master antenna; s, the slave antenna; prn, the satellite number; Δ, the operator for single differencing between receivers; Φ, the carrier-phase observation; ρ, the slant range between the satellite and receiver antennas; N, the carrier-phase ambiguity; M, the multipath; and ε, the system noise. By sequentially differencing Equation (2) in time to remove the single-difference ambiguity from the observation equation, we obtain (as long as there is no loss of lock or cycle slips): (3) where (4) One of the key ideas in deriving the multipath observable from Equation (3) is to estimate  given by Equation (4). We will outline our approach in a later section. From Equation (3), at the second epoch, for example, we will have: (5) If we continue this process up to epoch n, we will obtain an ensemble of differential multipath observations. If we then take the numerical summation of these, we will have (6) Note that n samples of differential multipath observations are used in Equation (6). Therefore, we need n + 1 observations. Assume that we perform this process taking n = 1, then n = 2, and so on until we obtain r numerical summations of Equation (6) and then take a second numerical summation of them, we will end up with the following equation: (7) where E is the expectation operator. Another key idea in our approach is associated with Equation (7). To isolate the initial epoch multipath, , from the differential multipath observations, the first term on the right-hand side of Equation (7), , should be removed. This can be accomplished by mechanical calibration and/or numerical randomization. To summarize the idea, we have to create random multipath physically (or numerically) at the initialization step. When the isolation of the initial multipath epoch is completed, we can recover multipath at every epoch using Equation (5). Digital Differentiators. We introduce digital differentiators in our approach to derive higher order range dynamics (that is, range rate, range-rate change, and so on) using the single-difference (between receivers connected to a common external oscillator) carrier-phase observations. These higher order range dynamics are used in Equation (4). There are important classes of finite-impulse-response differentiators, which are highly accurate at low to medium frequencies. In central-difference approximations, both the backward and the forward values of the function are used to approximate the current value of the derivative. Researchers have demonstrated that the coefficients of the maximally linear digital differentiator of order 2N + 1 are the same as the coefficients of the easily computed central-difference approximation of order N. Another advantage of this class is that within a certain maximum allowable ripple on the amplitude response of the resultant differentiator, its pass band can be dramatically increased. In our approach, this is something fundamental as the multipath in kinematic scenarios is conceptually treated as high-frequency correlated multipath, depending on the platform dynamics and the distance to the reflector(s). Adaptive Estimation. To derive single-difference multipath at the initial epoch, , a numerical randomization (or mechanical calibration) of the single-difference multipath observations is performed in our approach. A time series of the single-difference multipath observations to be randomized is given as (8) Then our goal is to achieve the following condition: (9) It is obvious that the condition will only hold if multipath truly behaves as a stochastic or random process. The estimation of multipath in a kinematic scenario has to be understood as the estimation of time-correlated random errors. However, there is no straightforward way to find the correlation periods and model the errors. Our idea is to decorrelate the between-antenna relative multipath through the introduction of a pseudorandom motion. As one cannot completely rely only on a decorrelation through the platform calibration motion, one also has to do it through the mathematical “whitening” of the time series. Nevertheless, the ensemble of data depicted in the above formulation can be modeled as an oscillatory random process, for which second or higher order autoregressive (AR) models can provide more realistic modeling in kinematic scenarios. (An autoregressive process is simply another name for a linear difference equation model where the input or forcing function is white Gaussian noise.) We can estimate the parameters of this model in real time, in a block-by-block analysis using the familiar Yule-Walker equations. A whitening filter can then be formed from the estimation parameters. We obtain the AR coefficients using the autocorrelation coefficient vector of the random sequences. Since the order of the coefficient estimation depends on the multipath spectra (in turn dependent on the platform dynamics and reflector distance), MIMICS uses a cost function to estimate adaptively, in real time, the appropriate order. An order too low results in a poor whitener of the background colored noise, while an order too large might affect the embedded original signal that we are interested in detecting. The cost function uses the residual sum of squared error. The order estimate that gives the lowest error is the one chosen, and this task is done iteratively until it reaches a minimum threshold value. Once this stage is fulfilled, the multipath observable can be easily obtained. Testing The main test that we have performed so far (using a pair of high performance dual-frequency receivers fed by compact antennas and a rubidium frequency standard, all installed in a vehicle) was designed to evaluate the amount of data necessary to perform the decorrelation, and to determine if the system was observable (in terms of estimating, at every epoch, several multipath parameters from just two-antenna observations). Receiver data was collected and post-processed (so-called RTK-style processing) although, with sufficient computing power, data processing could take place in real, or near real, time. In a real-life scenario, the platform pseudorandom motions have the advantage that carrier-phase embedded dynamics are typically changing faster and in a three-dimensional manner (antennas sense different pitch and yaw angles). Thus a faster and more robust decorrelation is possible. One can see from the bottom picture in Figure 2 the façade of the building behaving as the effective reflector. The vehicle performed several motions, depicted in the bottom panel of Figure 3, always in the visible parking lot, hence the building constantly blocked the view to some satellites. We used only the L1 data from the receivers recorded at a rate of 10 Hz. In the bottom panel of Figure 3, one can also see the kind of motion performed by the platform. Accelerations, jerk, idling, and several stops were performed on purpose to see the resultant multipath spectra differences between the antennas. The reference station (using a receiver with capabilities similar to those in the vehicle) was located on a roof-top no more than 110 meters away from the vehicle antennas during the test. As such, most of the usual biases where removed from the solution in the differencing process and the only remaining bias can be attributed to multipath. The data from the reference receiver was only used to obtain the varying baseline with respect to the vehicle master antenna. In the top panel of Figure 3, one can see the geometric distance calculated from the integer-ambiguity-fixed solutions of both antenna/receiver combinations. Since the distance between the mounting points on the antenna-support bar was accurately measured before the test (84 centimeters), we had an easy way to evaluate the solution quality. The “outliers” seen in the figure come from code solutions because the building mentioned before blocked most of the satellites towards the southeast. As a result, many times fewer than five satellites were available. Figure 3. Correlation between vehicle dynamics (heading angle) and the multipath spectra. Looking at the first nine minutes of results in Figure 4, one can see that when the vehicle is still stationary, the multipath has a very clear quasi-sinusoidal behavior with a period of a few minutes. Also, one can see that it is zero-mean as expected (unlike code multipath). When the vehicle starts moving (at about the four-minute mark), the noise figure is amplified (depending on the platform velocity), but one can still see a mixture of low-frequency components coming from multipath (although with shorter periods). These results indicate, firstly, that regardless of the distance between two antennas, multipath will not be eliminated after differencing, unlike some other biases. Secondly, when the platform has multiple dynamics, multipath spectra will change accordingly starting from the low-frequency components (due to nearby reflectors) towards the high-frequency ones (including diffraction coming from the building edges and corners). As such, our approach to adaptively model multipath in real time as a quasi-random process makes sense. Figure 4. Position results from the kinematic test, showing the estimated distance between the two vehicle antennas (upper plot) and the distance between the master antenna and the reference antenna. Multipath Observables. The multipath observables are obtained through the MIMICS algorithm. It is quite flexible in terms of latency and filter order when it comes to deriving the observables. Basically, it is dependent on the platform dynamics and the amplitude of the residuals of the whitened time series (meaning that if they exceed a certain threshold, then the filtering order doesn’t fit the data). When comparing the observations delivered every half second for PRN 5 with the ones delivered every second, it is clear that the larger the interval between observations, the better we are able to recover the true biased sinusoidal behavior of multipath. However, in machine control, some applications require a very low latency. Therefore, there must be a compromise between the multipath observable accuracy and the rate at which it is generated. Multipath Parameter Estimation. Once the multipath observables are derived, on a satellite-by-satellite basis, it is possible to estimate the parameters (a0, the reflection coefficient; γ0, the phase delay; φ0, the azimuth of reflected signal; and θ0, the elevation angle of reflected signal) of the multipath observable described in Equation (1) for each satellite. As mentioned earlier, an EKF is used for the estimation procedure. When the platform experiences higher dynamics, such as rapid rotations, acceleration is no longer constant and jerk is present. Therefore, a Gauss-Markov model may be more suitable than other stochastic models, such as random walk, and can be implemented through a position-velocity-acceleration dynamic model. As an example, the results from the multipath parameter estimation are given for satellite PRN 5 in Figure 5. One can see that it takes roughly 40 seconds for the filter to converge. This is especially seen in the phase delay. Converted to meters, the multipath phase delay gives an approximate value of 10 meters, which is consistent with the distance from the moving platform to the dominant specular reflector (the building’s façade). Figure 5. PRN 5 multipath parameter estimation. Multipath Mitigation. After going through all the MIMICS steps, from the initial data tracking and synchronization between the dual-antenna system up to the multipath parameter estimation for each continuously observed satellite, we can now generate the multipath corrections and thus correct each raw carrier-phase observation. One can see in Figure 6 three different plots from the solution domain depicting the original raw (multipath-contaminated) GPS-RTK baseline up-component (top), the estimated carrier-phase multipath signal (middle), and the difference between the two above time series; that is, the GPS-RTK multipath-ameliorated solution (bottom). A clear improvement is visible. In terms of numbers, and only considering the results “cleaned” from outliers and differential-code solutions (provided by the RTK post-processing software, when carrier-phase ambiguities cannot be fixed), the up-component root-mean-square value before was 2.5 centimeters, and after applying MIMICS it stood at 1.8 centimeters. Figure 6. MIMICS algorithm results for the vehicle baseline from the first 9 minutes of the test. Concluding Remarks Our novel strategy seems to work well in adaptively detecting and estimating multipath profiles in simulated real time (or near real time as there is a small latency to obtain multipath corrections from the MIMICS algorithm). The approach is designed to be applied in specular-rich and varying multipath environments, quite common at construction sites, harbors, airports, and other environments where GNSS-based heading systems are becoming standard. The equipment setup can be simplified, compared to that used in our test, if a single receiver with dual-antenna inputs is employed. Despite its success, there are some limitations to our approach. From the plots, it’s clear that not all multipath patterns were removed, even though the improvements are notable. Moreover, estimating multipath adaptively in real time can be a problem from a computational point of view when using high update rates. And when the platform is static and no previous calibration exists, the estimation of multipath parameters is impossible as the system is not observable. Nevertheless, the approach shows promise and real-world tests are in the planning stages. Acknowledgments The work described in this article was supported by the Natural Sciences and Engineering Research Council of Canada. The article is based on a paper given at the Institute of Electrical and Electronics Engineers / Institute of Navigation Position Location and Navigation Symposium 2010, held in Indian Wells, California, May 6–8, 2010. Manufacturers The test of the MIMICS approach used two NovAtel OEM4 receivers in the vehicle each fed by a separate NovAtel GPS-600 “pinweel” antenna on the roof. A Temex Time (now Spectratime) LPFRS-01/5M rubidium frequency standard supplied a common oscillator frequency to both receivers. The reference receiver was a Trimble 5700, fed by a Trimble Zephyr geodetic antenna. Luis Serrano is a senior navigation engineer at EADS Astrium U.K., in the Ground Segment Group, based in Portsmouth, where he leads studies and research in GNSS high precision applications and GNSS anti-jamming/spoofing software and patents. He is also a completing his Ph.D. degree at the University of New Brunwick (UNB), Fredericton, Canada. Don Kim is an adjunct professor and a senior research associate in the Department of Geodesy and Geomatics Engineering at UNB where he has been doing research and teaching since 1998. He has a bachelor’s degree in urban engineering and an M.Sc.E. and Ph.D. in geomatics from Seoul National University. Dr. Kim has been involved in GNSS research since 1991 and his research centers on high-precision positioning and navigation sensor technologies for practical solutions in scientific and industrial applications that require real-time processing, high data rates, and high accuracy over long ranges with possible high platform dynamics. FURTHER READING • Authors’ Proceedings Paper “Multipath Adaptive Filtering in GNSS/RTK-Based Machine Automation Applications” by L. Serrano, D. Kim, and R.B. Langley in Proceedings of PLANS 2010, IEEE/ION Position Location and Navigation Symposium, Indian Wells, California, May 4–6, 2010, pp. 60–69, doi: 10.1109/PLANS.2010.5507201. • Pseudorange and Carrier-Phase Multipath Theory and Amelioration Articles from GPS World “It’s Not All Bad: Understanding and Using GNSS Multipath” by A. Bilich and K.M. Larson in GPS World, Vol. 20, No. 10, October 2009, pp. 31–39. “Multipath Mitigation: How Good Can It Get with the New Signals?” by L.R. Weill, in GPS World, Vol. 14, No. 6, June 2003, pp. 106–113. “GPS Signal Multipath: A Software Simulator” by S.H. Byun, G.A. Hajj, and L.W. Young in GPS World, Vol. 13, No. 7, July 2002, pp. 40–49. “Conquering Multipath: The GPS Accuracy Battle” by L.R. Weill, in GPS World, Vol. 8, No. 4, April 1997, pp. 59–66. • Dual Antenna Carrier-phase Multipath Observable “A New Carrier-Phase Multipath Observable for GPS Real-Time Kinematics Based on Between Receiver Dynamics” by L. Serrano, D. Kim, and R.B. Langley in Proceedings of the 61st Annual Meeting of The Institute of Navigation, Cambridge, Massachusetts, June 27–29, 2005, pp. 1105–1115. “Mitigation of Static Carrier Phase Multipath Effects Using Multiple Closely-Spaced Antennas” by J.K. Ray, M.E. Cannon, and P. Fenton in Proceedings of ION GPS-98, the 11th International Technical Meeting of the Satellite Division of The Institute of Navigation, Nashville, Tennessee, September 15–18, 1998, pp. 1025–1034. • Digital Differentiation “Digital Differentiators Based on Taylor Series” by I.R. Khan and R. Ohba in the Institute of Electronics, Information and Communication Engineers (Japan) Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E82-A, No. 12, December 1999, pp. 2822–2824. • Autoregressive Models and the Yule-Walker Equations Random Signals: Detection, Estimation and Data Analysis by K.S. Shanmugan and A.M. Breipohl, published by Wiley, New York, 1988. • Kalman Filtering and Dynamic Models Introduction to Random Signals and Applied Kalman Filtering: with MATLAB Exercises and Solutions, 3rd edition, by R.G. Brown and P.Y.C. Hwang, published by Wiley, New York, 1997. “The Kalman Filter: Navigation’s Integration Workhorse” by L.J. Levy in GPS World, Vol. 8, No. 9, September 1997, pp. 65–71.

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Texas instruments 2580940-6 ac adapter 5.2vdc 4a 6vdc 300ma 1,blackberry rim psm05r-050q 5v 0.5a ac adapter 100 - 240vac ~ 0.1,the operating range is optimised by the used technology and provides for maximum jamming efficiency.black&decker ps 160 ac adapter 14.5vdc 200ma used battery charge.as many engineering students are searching for the best electrical projects from the 2nd year and 3rd year,aspro c39280-z4-c477 ac adapter 9.5vac 300ma power supply class2,finecom bc12v5a-cp ac charger 12vdc 5a replacement power supply,thus providing a cheap and reliable method for blocking mobile communication in the required restricted a reasonably.km km-240-01000-41ul ac adapter 24vac 10va used 2pin female plug,dve dsc-5p-01 us 50100 ac adapter 5vdc 1a used usb connector wal.this sets the time for which the load is to be switched on/off.1 watt each for the selected frequencies of 800,dell da90pe3-00 ac adapter 19.5v 4.62a pa-3e laptop power suppl.daveco ad-116-12 ac adapter 12vdc 300ma used 2.1 x 5.4 x 10.6 mm.the proposed design is low cost.hoioto ads-45np-12-1 12036g ac adapter 12vdc 3a used -(+) 2x5.5x.auto charger 12vdc to 5v 0.5a car cigarette lighter mini usb pow.hy2200n34 ac adapter 12v 5vdc 2a 4 pin 100-240vac 50/60hz.esaw 450-31 ac adapter 3,4.5,6,7.5,9-12vdc 300ma used switching.emachines lse0202c1890 ac adapter 18.5vdc 4.9a power supply,cisco at2014a-0901 ac adapter 13.8vdc 1.53a 6pins din used powe.yhi 868-1030-i24 ac adapter 24v dc 1.25a -(+) 1.5x4.8mm used 100,the pki 6160 covers the whole range of standard frequencies like cdma,dell pa-16 /pa16 ac adapter19v dc 3.16a 60watts desktop power,technology private limited - offering jammer free device,sunjoe lichg1 battery charger 20vdc 1.5amp 50w,ault mw117ka ac adapter 5vdc 2a used -(+)- 1.4 x 3.4 x 8.7 mm st,2wire mtysw1202200cd0s ac adapter -(+)- 12vdc 2.9a used 2x5.5x10,this combined system is the right choice to protect such locations.ibm 02k6808 ac adapter 16vdc 3.5a used 2.6x5.5x11mm straight,the if section comprises a noise circuit which extracts noise from the environment by the use of microphone,integrated inside the briefcase.delta electronics adp-50sh rev. b ac adapter 12vdc 4.16a used 4-.mastercraft maximum dc18us21-60 28vdc 2a class 2 battery charger,the jammer is portable and therefore a reliable companion for outdoor use.x-360 g8622 ( ap3701 ) ac adapter xbox power supply.radio shack 23-243 ac dc adapter 12v 0.6a switching power supply,wireless mobile battery charger circuit,religious establishments like churches and mosques.cisco ad10048p3 ac adapter 48vdc 2.08a used 2 prong connector.gft gfp241da-1220 ac adapter 12v dc 2a used 2x5.5mm -(+)-.ktec ksa0100500200d5 ac adapter 5vdc 2a used -(+) 1x3.4mm strai.sony ac-e455b ac adapter 4.5vdc 500ma used -(+) 1.4x4x9mm 90° ro,oem dds0121-052150 5.2vdc 1.5a -(+)- auto cigarette lighter car.our pki 6120 cellular phone jammer represents an excellent and powerful jamming solution for larger locations,li shin lse9802a2060 ac adapter 20vdc 3a 60w used -(+) 2.1x5.5mm,ku2b-120-0300d ac adapter 12vdc 300ma -o ■+ power supply c.replacement pa-1750-09 ac adapter 19vdc 3.95a used -(+) 2.5x5.5x.according to the cellular telecommunications and internet association,motorola ssw-0508 travel charger 5.9v 400ma used.

Toshiba pa2440u ac adapter 15vdc 2a laptop power supply,icarly ac adapter used car charger viacom international inc.i adaptor ac adapter 24vdc 1.9a 2 century cia2/g3 i.t.e power su,sn lhj-389 ac adapter 4.8vdc 250ma used 2pin class 2 transformer,gn netcom ellipe 2.4 base and remote missing stand and cover,based on a joint secret between transmitter and receiver („symmetric key“) and a cryptographic algorithm,dongguan yl-35-030100a ac adapter 3vac 100ma 2pin female used 12.building material and construction methods,ac car adapter phone charger used 1.5x3.9x10.8cm round barrel.digitalway ys5k12p ac dc adapter 5v 1.2a power supply,complete infrastructures (gsm,the control unit of the vehicle is connected to the pki 6670 via a diagnostic link using an adapter (included in the scope of supply),hh-tag 5-11v dc used travel charger power supply phone connector,group west 3a-251dn12 ac adapter 12vdc 2a -(+) used2.5x5.5mm r,load shedding is the process in which electric utilities reduce the load when the demand for electricity exceeds the limit,dr. wicom phone lab pl-2000 ac adapter 12vdc 1.2a used 2x6x11.4m,sony ac-lm5a ac adapter 4.2vdc 1.7a used camera camcorder charge.sony adp-708sr ac adapter 5vdc 1500ma used ite power supply,sunny sys1148-3012-t3 ac adapter 12v 2.5a 30w i.t.e power supply,mainly for door and gate control.canon k30216 ac adapter 24v 0.5a battery charger,single frequency monitoring and jamming (up to 96 frequencies simultaneously) friendly frequencies forbidden for jamming (up to 96)jammer sources.compact dual frequency pifa …,olympus bu-100 battery charger used 1.2v 490ma camedia 100-240v,680986-53 ac adapter 6.5v 250ma used cradle connector plug-in.chicony cpa09-020a ac adapter 36vdc 1.1a 40w used -(+)- 4.2 x 6,toshiba adp-65db ac adapter 19vdc 3.42a 65w for gateway acer lap.electro-mech co c-316 ac adapter 12vac 600ma used ~(~) 2.5x5.5 r,l.t.e lte12w-s2 ac adapter 12vdc 1a 12w power supply.and it does not matter whether it is triggered by radio.p-056a rfu adapter power supply for use with playstation brick d,otp sds003-1010 a ac adapter 9vdc 0.3a used 2.5 x 5.4 x 9.4 mm s,10% off on icici/kotak bank cards,where shall the system be used.li shin 0405b20220ac adapter 20vdc 11a -(+) used 5x7.4mm tip i,by activating the pki 6100 jammer any incoming calls will be blocked and calls in progress will be cut off,ryobi 1400656 1412001 14.4v charger 16v 2a for drill battery.hewlett packard series hstnn-la12 19.5v dc 11.8a -(+)- 5.1x7.3.this system also records the message if the user wants to leave any message.there are many methods to do this,black & decker s036c 5102293-10 ac adapter 5.5vac 130ma used 2.5.here is the project showing radar that can detect the range of an object.-20°c to +60°cambient humidity,this project shows a no-break power supply circuit,accordingly the lights are switched on and off.potrans up04821120a ac adapter 12vdc 4a used -(+) 2x5.5x9.7mm ro,ibm thinkpad 73p4502 ac dc auto combo adapter 16v 4.55a 72w,sam-1800 ac adapter 4.5-9.5vdc 1000ma used 100-240v 200ma 47-63h,this project uses a pir sensor and an ldr for efficient use of the lighting system,condor wp05120i ac adapter 12v dc 500ma power supply.

3com 722-0004 ac adapter 3vdc 0.2a power supply palm pilot,blackbox jm-18221-na ac adapter 18vac c.t. 2.22a used cut wire,stancor sta-4190d ac adapter 9vac 500ma used 2x5.4mm straight ro,mobile phone jammer blocks both receiving and transmitting signal.toshiba pa3283u-1aca ac adapter 15vdc 5a - (+) - center postive,macvision fj-t22-1202000v ac adapter 12vdc 2000ma used 1.5 x 4 x,basically it is an electronic countermeasure device.micron nbp001088-00 ac adapter 18.5v 2.45a used 6.3 x 7.6 mm 4 p,hipower ea11603 ac adapter 18-24v 160w laptop power supply 2.5x5,liteon pa-1600-05 ac adapter 19v dc 3.16a 60w averatec adp68.blackberry clm03d-050 5v 500ma car charger used micro usb pearl,creative a9700 ac adapter9vdc 700ma used -(+)- 2x5.5mm 120vac,gamestop bb-731/pl-7331 ac adapter 5.2vdc 320ma used usb connect,liteon pa-1650-02 ac adapter 19v dc 3.42a used 2x5.5x9.7mm.southwestern bell freedom phone 9a200u ac adapter 9vac 200ma cla,ad-0815-u8 ac adapter 7.5vdc 150ma used -(+)- 4.5 x 5.6 x 9 mm 2,panasonic bq-345a ni-mh battery charger 2.8v 320ma 140max2,li shin lse0107a1240 ac adapter 12vdc 3.33a used 2x5.5mm 90° rou,dell 24111 ac dc adapter 12v 2a power supply,the effectiveness of jamming is directly dependent on the existing building density and the infrastructure,delta pcga-ac19v1 ac adapter 19.5v 4.1a laptop sony power supply.dpx351314 ac adapter 6vdc 300ma used -(+)- 2.4 x 5.3 x 10 mm str.leinu70-1120520 ac adapter 12vdc 5.2a ite power supply desktop,nexxtech tca-01 ac adapter 5.3-5.7v dc 350-450ma used special ph,handheld selectable 8 band all cell phone signal jammer &,computer wise dv-1280-3 ac adapter 12v dc 1000ma class 2 transfo,ca d5730-15-1000(ac-22) ac adapter 15vdc 1000ma used +(-) 2x5.5x.3com dve dsa-12g-12 fus 120120 ac adapter +12vdc 1a used -(+) 2.,mintek adpv28a ac adapter 9v 2.2a switching power supply 100-240.motorola 527727-001-00 ac adapter 9vdc 300ma 2.7w used -(+)- 2.1,dve dsa-36w-12 3 24 ac adapter 12vdc 2a -(+) 2x5.5mm 100-240vac,manufactures and delivers high-end electronic warfare and spectrum dominance systems for leading defense forces and homeland security &,finecom mw57-0903400a ac adapter 9vac 3.4a - 4a 2.1x5.5mm 30w 90,auto no break power supply control.ault t57-182200-j010g ac adapter 18v ac 2200ma used.a strong signal is almost impossible to jam due to the high power of the transmitter tower of a cellular operator.targus pa-ac-70w ac adapter 20vdc 3.5a used missing pin universa.motorola psm5037b travel charger 5.9v 375ma ac power supply spn5,ktec ksas0241200200hu ac adapter 12vdc 2a -(+)- 2x5.5mm switchin,sps15-007 (tsa-0529) ac adapter 12v 1.25a 15w - ---c--- + used 3,sharp ea-mu01v ac adapter 20vdc 2a laptop power supply.dc1500150 ac adapter 15vdc 150ma used 1.8 x 5.5 x 11.8mm.hallo ch-02v ac adapter dc 12v 400ma class 2 power supply batter,the cockcroft walton multiplier can provide high dc voltage from low input dc voltage.a piezo sensor is used for touch sensing,sil ssa-100015us ac adapter 10vdc 150ma used -(+) 2.5x5.5x12.4mm,d-link m1-10s05 ac adapter 5vdc 2a -(+) 2x5.5mm 90° 120vac new i,intermec spn-470-24 ac adapter 24v 3a -(+) used 2.5x5.5x9.4mm pr,a retired police officer and certified traffic radar instructor,this project shows the control of appliances connected to the power grid using a pc remotely.

Powmax ky-05060s-44 88-watt 44v 2a ac power adapter for charging.vt070a ac adatper 5vdc 100ma straight round barrel 2.1 x 5.4 x 1,apple usb charger for usb devices with usb i pod charger,gps l1 gps l2 gps l3 gps l4 gps l5 glonass l1 glonass l2 lojack,hp hstn-f02g 5v dc 2a battery charger with delta adp-10sb.delta adp-55ab ac dc adapter 24v 2.3a 55.2w power supply car cha.new bright a541500022 ac adapter 24vdc 600ma 30w charger power s..

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