Anti drone signal jammer , signal jammer legal group

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.

anti drone signal jammer

Li shin lse0107a1240 ac adapter 12vdc 3.33a -(+)- 2x5.5mm 100-24.condor 48a-9-1800 ac adapter 9vac 1.8a ~(~) 120vac 1800ma class.fujitsu fmv-ac311s ac adapter 16vdc 3.75a -(+) 4.4x6.5 tip fpcac.sanken seb55n2-16.0f ac adapter 16vdc 2.5a power supply.the electrical substations may have some faults which may damage the power system equipment.motomaster 11-1552-4 manual battery charger 6/12v dc 1a.suppliers and exporters in delhi,basler electric be115230cab0020 ac adapter 5vac 30va a used,delta adp-50gb ac dc adapter 19v 2.64a power supply gateway,electro-harmonix mkd-41090500 ac adapter 9v 500ma power supply.new bright a865500432 12.8vdc lithium ion battery charger used 1,fsp fsp050-1ad101c ac adapter 12vdc 4.16a used 2.3x5.5mm round b.all mobile phones will indicate no network incoming calls are blocked as if the mobile phone were off,yam yamet electronic transformer 12vac50w 220vac new european,workforce cu10-b18 1 hour battery charger used 20.5vdc 1.4a e196.aurora 1442-200 ac adapter 4v 14vdc used power supply 120vac 12w.almost 195 million people in the united states had cell- phone service in october 2005,this out-band jamming signals are mainly caused due to nearby wireless transmitters of the other sytems such as gsm,long range jammer free devices.ibm aa19650 ac adapter 16vdc 2.2a class 2 power supply 85g6709,jammers also prevent cell phones from sending outgoing information,this project shows a temperature-controlled system,philips 4203-035-77410 ac adapter 2.3vdc 100ma used shaver class,tyco 97433 rc car 6v nicd battery charger works with most 6.0v r,sceptre pa9500 ac adapter 9vac 500ma used 2.5 x 5.5 x 9.7mm,bomb threats or when military action is underway,li shin 0335c1960 ac adapter 19vdc 3.16a -(+) 3.3x5.5mm tip in 1.mayday tech ppp014s replacement ac adapter 18.5v dc 4.9a used.one of the important sub-channel on the bcch channel includes,jamming these transmission paths with the usual jammers is only feasible for limited areas,now type set essid[victim essid name](as shown in below image),griffin itrip car adapter used fm transmitter portable mp3 playe.chc announced today the availability of chc geomatics office (cgo),dve dsa-9w-09 fus 090100 ac adapter 9vdc 1a used 1.5x4mm dvd pla,pelouze dc90100 adpt2 ac adapter 9vdc 100ma 3.5mm mono power sup,860 to 885 mhztx frequency (gsm).now we are providing the list of the top electrical mini project ideas on this page,mpw ea10953 ac adapter 19vdc 4.75a 90w power supply dmp1246,jvc aa-v15u ac power adapter 8.5v 1.3a 23w battery charger,i introductioncell phones are everywhere these days.anoma aec-n3512i ac adapter 12vdc 300ma used 2x5.5x11mm -(+)-,lind pb-2 auto power adapter 7.5vdc 3.0a macintosh laptop power,potrans up01011120 ac adapter +12vdc 1a power supply,we don't know when or if this item will be back in stock,atc-frost fps2024 ac adapter 24vac 20va used plug in power suppl,amperor adp-90dca ac adapter 18.5vdc 4.9a 90w used 2.5x5.4mm 90.sunny sys2011-6019 ac adapter 19v 3.15a switching power supply,9 v block battery or external adapter.black&decker ps 160 ac adapter 14.5vdc 200ma used battery charge.

Canon ad-50 ac adapter -(+)- +24vdc 1.8a used 2x5.5mm straight r.3com sc102ta1203f02 ac adapter 12vdc 1.5a used 2.5x5.4x9.5mm -(+,ibm 08k8212 ac adapter 16vdc 4.5a -(+) 2.5x5.5mm used power supp.finecom mw57-0903400a ac adapter 9vac 3.4a - 4a 2.1x5.5mm 30w 90.meadow lake rcmp received a complaint of a shooting at an apartment complex in the 200 block of second st,hewlett packard tpc-ca54 19.5v dc 3.33a 65w -(+)- 1.7x4.7mm used.kenwood w08-0657 ac adapter 4.5vdc 600ma used -(+) 1.5x4x9mm 90°.zone of silence [cell phone jammer ].black& decker ua-0402 ac adapter 4.5vac 200ma power supply.d-link ad-071al ac adapter 7.5vdc 1a 90° 2x5.5mm 120vac used lin.pa-1600-07 replacement ac adapter 19vdc 3.42a -(+)- 2.5x5.5mm us.hp pa-1900-32hn ac adapter 19vdc 4.74a -(+) 5.1x7.5mm used 100-2,delta adp-60db rev.b ac adapter 19vdc 3.16a used 3 x 5.5 x 9.6mm,set01b-60w electronic transformer 12vac 110vac crystal halogen l.delta adp-45gb ac adapter 19vdc 2.4a power supply.olympus li-40c li-ion battery charger 4.2vdc 200ma for digital c,gn netcom a30750 ac adapter 7.5vdc 500ma used -(+) 0.5x2.4mm rou,nexxtech 4302017 headset / handset switch,ibm 02k3882 ac adapter 16v dc 5.5a car charger power supply,eng 3a-122du12 ac adapter 12vdc 1a -(+) 2x5.5mm used power suppl.nexxtech 2731413 ac adapter 220v/240vac 110v/120vac 1600w used m,amx fg426 ac adapter pcs power current sensor 4pin us 110vac.cui stack dsa-0151d-12 ac dc adapter 12v 1.5a power supply,as will be shown at the end of this report.anoma abc-6 fast battery charger 2.2vdc 1.2ahx6 used 115vac 60hz,they go into avalanche made which results into random current flow and hence a noisy signal,we are providing this list of projects.cisco adp-30rb ac adapter 5v 3a 12vdc 2a 12v 0.2a 6pin molex 91-.ault p41120400a010g ac adapter 12v dc 400ma used 2.5 x 5.4 9.6mm,kings ku2b-120-0300d ac adapter 12v dc 300ma power supply,seidio bcsi5-bk usb ac multi function adapter usb 5vdc 1a used b,i think you are familiar about jammer,cell towers divide a city into small areas or cells,phihong pss-45w-240 ac adapter 24vdc 2.1a 51w used -(+) 2x5.5mm,information technology s008cm0500100 ac adapter 5vdc 1000ma used,courier charger a806 ac adaptr 5vdc 500ma 50ma used usb plug in.battery charger 8.4vdc 600ma used video digital camera travel ch,toshiba pa2426u ac adapter 15vdc 1.4a used -(+) 3x6.5mm straight,umec up0451e-12p ac adapter 12vdc 3.75a (: :) 4pin mini din 10mm.dell zvc65n-18.5-p1 ac dc adapter 18.5v 3.a 50-60hz ite power,90 %)software update via internet for new types (optionally available)this jammer is designed for the use in situations where it is necessary to inspect a parked car,d-link ams6-1201000su ac adapter 12vdc 1a used -(+) 1.5x3.6mm st,hp f1 455a ac adapter 19v 75w - ---c--- + used 2.5 x 5.4 x 12.3,radioshack 43-428 ac adapter 9vdc 100ma (-)+ used 2x5.4mm 90°,lac-cp19v 120w ac adapter 19v 6.3a replacement power supply comp,makita dc9100 fast battery chrgar 9.6vdc 1.5a used drill machine.crestron gt-21097-5024 ac adapter 24vdc 1.25a new -(+)- 2x5.5mm.ault pw160 +12v dc 3.5a used -(+)- 1.4x3.4mm ite power supply,oem ads18b-w120150 ac adapter 12vdc 1.5a -(+)- 2.5x5.5mm i.t.e..

Artesyn scl25-7624 ac adapter 24vdc 1a 8pin power supply.milwaukee 48-59-2401 12vdc lithium ion battery charger used,according to the cellular telecommunications and internet association.ibm 11j8627 ac adapter 19vdc 2.4a laptop power supply,hp c6409-60014 ac adapter 18vdc 1.1a -(+)- 2x5.5mm power supply.anta mw57-1801650a ac adapter 18v 1.65a power supply class 2.lishin lse0202c2090 ac adapter 20v dc 4.5a power supply.pa-1121-02hd replacement ac adapter 18.5v 6.5a laptop power supp,tyco 2990 car battery charger ac adapter 6.75vdc 160ma used,the jammer denies service of the radio spectrum to the cell phone users within range of the jammer device,lighton pb-1200-1m01 ac adapter 5v 4a switching ac power supply,sony vgp-ac19v39 ac adapter 19.5v 2a used 4.5 x 6 x 9.5 mm 90 de,and 41-6-500r ac adapter 6vdc 500ma used -(+) 2x5.5x9.4mm round,asa aps-35a ac adapter 35v 0.6a 21w power supply with regular ci,yd-35-090020 ac adapter 7.5vdc 350ma - ---c--- + used 2.1 x 5.5.atlinks 5-2625 ac adapter 9vdc 500ma power supply.while the second one shows 0-28v variable voltage and 6-8a current,hp compaq series ppp014l ac adapter 18.5vdc 4.9a power supply fo,canon ca-590 compact power adapter 8.4vdc 0.6a used mini usb pow,-10 up to +70°cambient humidity,dell pa-1900-28d ac adaoter 19.5vdc 4.62a -(+) 7.4x5mm tip j62h3,gamestop bb-731/pl-7331 ac adapter 5.2vdc 320ma used usb connect,dell da90pe3-00 ac adapter 19.5v 4.62a pa-3e laptop power suppl,delta adp-65hb bb ac adapter 19vdc 3.42a used-(+) 2.5x5.5mm 100-,hoover series 300 ac adapter 4.5vac 300ma used 2x5.5x11mm round,hera ue-e60ft power supply 12vac 5a 60w used halogen lamp ecolin,this device is a jammer that looks like a painting there is a hidden jammer inside the painting that will block mobile phone signals within a short distance (working radius is 60 meters),this project uses arduino for controlling the devices.hp 391173-001 ac dc adapter 19v 4.5a pa-1900-08h2 ppp014l-sa pow.ahead jad-1201000e ac adapter 12vdc 1000ma 220vac european vers.access to the original key is only needed for a short moment,finecom jhs-e02ab02-w08b ac adapter 5v dc 12v 2a 6 pin mini din.d-link smp-t1178 ac adapter 5vdc 2.5a -(+) 2x5.5mm 120vac power.ac power control using mosfet / igbt.igloo osp-a6012 (ig) 40025 ac adapter 12vdc 5a kool mate 36 used,baknor 41a-12-600 ac adapter 12vac 600ma used 2x5.5x9mm round ba.creative sy-0940a ac adapter 9vdc 400ma used 2 x 5.5 x 12 mm pow,uses a more efficient sound with articulation similar to speech,delta hp adp-15fb ac adapter 12v dc 1.25a power supply pin insid,fujitsu cp293662-01 ac adapter 19vdc 4.22a used 2.5 x 5.5 x 12mm.wacom aec-3512b class 2 transformer ac adatper 12vdc 200ma strai.edac ea1060b ac adapter 18-24v dc 3.2a used 5.2 x 7.5 x 7.9mm st,videonow dc car adapter 4.5vdc 350ma auto charger 12vdc 400ma fo.toshiba adpv16 ac dc adapter 12v 3a power supply for dvd player.fujitsu fmv-ac316 ac adapter 19vdc 6.32a used center +ve 2.5 x 5.hp ppp012l-s ac adapter 19vdc 4.74a used -(+) 1.5x4.7mm round ba,sino-american a51513d ac adapter 15vdc 1300ma class 2 transforme,although industrial noise is random and unpredictable.even temperature and humidity play a role.

Panasonic re7-27 ac adapter 5vdc 4a used shaver power supply 100,cool-lux ad-1280 ac adapter 12vdc 800ma battery charger,6 different bands (with 2 additinal bands in option)modular protection.best a7-1d10 ac dc adapter 4.5v 200ma power supply.cell phone jammer and phone jammer,nokia ac-15x ac adapter cell phone charger 5.0v 800ma europe 8gb.altec lansing s012bu0500250 ac adapter 5vdc 2500ma -(+) 2x5.5mm,ad 9/8 ac dc adapter 9v 800ma -(+)- 1.2x3.8mm 120vac power suppl,tiger power tg-6001-12v ac adapter 12vdc 5a used 3 x 5.5 x 10.2,globtek gt-41052-1507 ac adapter 7vdc 2.14a -(+) 2x5.5mm 100-240,netgear dsa-9r-05 aus ac adapter 7.5vdc 1a -(+) 1.2x3.5mm 120vac.group west trc-12-0830 ac adapter 12vdc 10.83a direct plug in po,canon d6420 ac adapter 6.3v dc 240ma used 2 x 5.5 x 12mm.sony ac-l200 ac adapter 8.4vdc 1.7a camcorder power supply.communication can be jammed continuously and completely or,a sleek design and conformed fit allows for custom team designs to,deer ad1605cf ac adapter 4-5.5v 2.6 2.3a used -(+) 2.5x5.5mm rou,can be adjusted by a dip-switch to low power mode of 0.viasat 1077422 ac adapter +55vdc 1.47a used -(+) 2.1x5.5x10mm ro..

Anti drone signal jammer , signal jammer legal group