Enhancing GNSS Receiver Sensitivity by Combining Signals from Multiple Satellites By Penina Axelrad, James Donna, Megan Mitchell, and Shan Mohiuddin A new approach to enhancing signal sensitivity combines the received signal power from multiple satellites in a direct-to-navigation solution. INNOVATION INSIGHTS by Richard Langley ALTHOUGH I HAVE MANAGED the Innovation column continuously since GPS World’s first issue, it wasn’t until the second issue that I authored a column article. That article, co-written with Alfred Kleusberg, was titled “The Limitations of GPS.” It discussed some of the then-current problems of GPS, including poor signal reception, loss of signal integrity, and limited positioning accuracy. In the ensuing 20 years, both signal integrity and positioning accuracy have improved significantly. Advances in the GPS control segment’s capabilities to continuously monitor and assess signal performance, together with receiver-autonomous integrity monitoring and integrity enhancement provided by augmentation systems, have reduced worries about loss of signal integrity. The removal of Selective Availability and use of error corrections provided by augmentation systems, among other approaches, have improved positioning accuracy. But the problem of poor reception due to weak signals is still with us. In that March/April 1990 article, we wrote “[GPS] signals propagate from the satellites to the receiver antenna along the line of sight and cannot penetrate water, soil, walls, or other obstacles very well. … In surface navigation and positioning applications, the signal can be obstructed by trees, buildings, and bridges. … [In] the inner city streets of urban areas lined with skyscrapers, the ‘visibility’ of the GPS satellites is very limited. In such areas, the signals can be obstructed for extended periods of time or even [be] continuously unavailable.” Poor signal reception in other than open-sky environments is still a problem with conventional GPS receivers. However, extending signal integration times and using assisted-GPS techniques can give GPS some degree of capability to operate indoors and in other restricted environments, albeit typically with reduced positioning accuracy. An antenna with sufficient gain is needed and capable systems are available on the market. The pilot channels of modernized GNSS signals will also benefit signal acquisition and tracking in challenging environments. In this month’s column, we look at a completely different approach to enhancing signal sensitivity. Rather than requiring each satellite’s signal to be acquired and tracked before it can be used in the navigation solution, the new approach — dubbed “collective detection” — combines the received signal power from multiple satellites in a direct-to-navigation-solution procedure. Besides providing a quick coarse position solution with weak signals, this approach can be used to monitor the signal environment, aid deeply-coupled GPS/inertial navigation, and assist with terrain and feature recognition. “Innovation” features discussions about advances in GPS technology, its applications, and the fundamentals of GPS positioning. The column is coordinated by Richard Langley, Department of Geodesy and Geomatics Engineering, University of New Brunswick. Growing interest in navigating indoors and in challenging urban environments is motivating research on techniques for weak GPS signal acquisition and tracking. The standard approach to increasing acquisition and tracking sensitivity is to lengthen the coherent integration times, which can be accomplished by using the pilot channels in the modernized GPS signals or by using assisted GPS (A-GPS) techniques. These techniques operate in the traditional framework of independent signal detection, which requires a weak signal to be acquired and tracked before it is useful for navigation. This article explores a complementary, but fundamentally different, approach that enhances signal sensitivity by combining the received power from multiple GPS satellites in a direct-to-navigation-solution algorithm. As will be discussed in the following sections, this collective detection approach has the advantage of incorporating into the navigation solution information from signals that are too weak to be acquired and tracked, and it does so with a modest amount of computation and with no required hardware changes. This technology is appropriate for any application that requires a navigation solution in a signal environment that challenges traditional acquisition techniques. Collective detection could be used to monitor the signal environment, aid deeply coupled GPS/INS during long outages, and help initiate landmark recognition in an urban environment. These examples are explained further in a subsequent section. In order to understand how the collective detection algorithm works, it is instructive to first consider the traditional approach to acquisition and tracking. Acquisition Theory and Methods In a typical stand-alone receiver, the acquisition algorithm assesses the signal’s correlation power in discrete bins on a grid of code delay and Doppler frequency (shift). The correlation calculations take the sampled signal from the receiver’s RF front end, mix it with a family of receiver-generated replica signals that span the grid, and sum that product to produce in-phase (I) and quadrature (Q) correlation output. The correlation power is the sum of the I and Q components, I2 + Q2. Plotting the power as a function of delay and frequency shift produces a correlogram, as shown in FIGURE 1. It should be noted that both correlation power and its square root, the correlation amplitude, are found in the GPS literature. For clarity, we will always use the correlation power to describe signal and noise values. If a sufficiently powerful signal is present, a distinct peak appears in the correlogram bin that corresponds to the GPS signal’s code delay and Doppler frequency. If the peak power exceeds a predefined threshold based on the integration times and the expected carrier-to-noise spectral density, the signal is detected. The code delay and Doppler frequency for the peak are then passed to the tracking loops, which produce more precise measurements of delay — pseudoranges — from which the receiver’s navigation solution is calculated. When the satellite signal is attenuated, however, perhaps due to foliage or building materials, the correlation peak cannot be distinguished and the conventional approach to acquisition fails. The sensitivity of traditional tracking algorithms is similarly limited by the restrictive practice of treating each signal independently. More advanced tracking algorithms, such as vector delay lock loops or deeply integrated filters, couple the receiver’s tracking algorithms and its navigation solution in order to take advantage of the measurement redundancy and to leverage information gained from tracking strong signals to track weak signals. The combined satellite detection approach presented in this article extends the concept of coupling to acquisition by combining the detection and navigation algorithms into one step. Collective Detection In the collective detection algorithm, a receiver position and clock offset grid is mapped to the individual GPS signal correlations, and the combined correlation power is evaluated on that grid instead of on the conventional independent code delay and Doppler frequency grids. The assessment of the correlation power on the position and clock offset grid leads directly to the navigation solution. The mapping, which is key to the approach, requires the receiver to have reasonably good a priori knowledge of its position, velocity, and clock offset; the GPS ephemerides; and, if necessary, a simplified ionosphere model. Given this knowledge, the algorithm defines the position and clock offset search grid centered on the assumed receiver state and generates predicted ranges and Doppler frequencies for each GPS signal, as illustrated in FIGURE 2. The mapping then relates each one of the position and clock offset grid points to a specific code delay and Doppler frequency for each GPS satellite, as illustrated in FIGURE 3. Aggregating the multiple delay/Doppler search spaces onto a single position/clock offset search space through the mapping allows the navigation algorithm to consider the total correlation power of all the signals simultaneously. The correlation power is summed over all the GPS satellites at each position/clock-offset grid point to create a position domain correlogram. The best position and clock-offset estimates are taken as the grid point that has the highest combined correlation power. This approach has the advantage of incorporating into the position/clock-offset estimate information contained in weak signals that may be undetectable individually using traditional acquisition/tracking techniques. It should be noted that a reasonable a priori receiver state estimate restricts the size of the position and clock-offset grid such that a linear mapping, based on the standard measurement sensitivity matrix used in GPS positioning, from the individual signal correlations, is reasonable. Also, rather than attempt to align the satellite correlations precisely enough to perform coherent sums, noncoherent sums of the individual satellite correlations are used. This seems reasonable, given the uncertainties in ranging biases between satellites, differences and variability of the signal paths through the ionosphere and neutral atmosphere, and the large number of phases that would have to be aligned. Applications The most obvious application for collective detection is enabling a navigation fix in circumstances where degraded signals cause traditional acquisition to fail. The sweet spot of collective detection is providing a rapid but coarse position solution in a weak signal environment. The solution can be found in less time because information is evaluated cohesively across satellites. This is especially clear when the algorithm is compared to computationally intensive long integration techniques. There are several ways that collective detection can support urban navigation. This capability benefits long endurance users who desire a moderate accuracy periodic fix for monitoring purposes. In some circumstances, the user may wish to initiate traditional tracking loops for a refined position estimate. However, if the signal environment is unfavorable at the time, this operation will waste valuable power. The collective detection response indicates the nature of the current signal environment, such as indoors or outdoors, and can inform the decision of whether to spend the power to transition to full GPS capabilities. In urban applications, deeply integrated GPS/INS solutions tolerate GPS outages by design. However, if the outage duration is too long, the estimate uncertainty will eventually become too large to allow conclusive signal detection to be restored. Running collective detection as a background process could keep deeply integrated filters centered even in long periods of signal degradation. Because collective detection approaches the acquisition problem from a position space instead of the individual satellite line-of-sight space, it provides inherent integrity protection. In the traditional approach, acquiring a multipath signal will pollute the overall position fix. In collective detection, such signals are naturally exposed as inconsistent with the position estimate. Another use would be to initialize landmark correlation algorithms in vision navigation. Landmark correlation associates street-level video with 3D urban models as an alternative to (GPS) absolute position and orientation updates. This technique associates landmarks observed from ground-level imagery with a database of landmarks extracted from overhead-derived 3D urban models. Having a coarse position (about 100 meters accuracy) enhances initialization and restart of the landmark correlation process. Draper Laboratory is planning to demonstrate the utility of using collective detection to enable and enhance landmark correlation techniques for urban navigation. In all of these applications, collective detection is straightforward to implement because it simply uses the output of correlation functions already performed on GPS receivers. Simulations and Processing The new algorithm has been tested using live-sky and simulated data collected by a Draper Laboratory wideband data recorder. A hardware GPS signal simulator was used to simulate a stationary observer receiving 11 equally powered GPS signals that were broadcast from the satellite geometry shown in FIGURE 4. The data recorder and the signal simulator were set up in a locked-clock configuration with all of the simulator’s modeled errors set to zero. No frequency offsets should exist between the satellites and the receiver. A clock bias, however, does exist because of cable and other fixed delays between the two units. The data recorder houses a four-channel, 14-bit A/D module. It can support sample rates up to 100 MHz. For this work, it was configured to downconvert the signal to an IF of 420 kHz and to produce in-phase and quadrature samples at 10 MHz. Results and Discussion To combine satellites, a position domain search space is established, centered on the correct location and receiver clock bias. A grid spacing of 30 meters over a range of ± 900 meters in north and east directions, and ± 300 meters in the vertical. In the first simulated example, the correlation power for all the satellites is summed on the position grid using a single 1-millisecond integration period. In this case, the true carrier-to-noise-density ratio for each signal is 40 dB-Hz. The results are shown in FIGURE 5. The plots in the left panel show the individual signal correlations as a function of range error. The four plots in the upper-right panel show several views of the combined correlation as a function of position error. The upper-left plot in the panel shows the correlation value as a function of the magnitude of the position error. The upper-right plot shows the correlation as a function of the north-east error, the lower-left the north-down error, and the lower-right the east-down error. Notice how the shape of the constant power contours resembles the shape of the constant probability contours that would result from a least-squares solution’s covariance matrix. The final plot, the bottom-right panel, shows a 3D image of the correlation power as a function of the north-east error. It is clear in these images that in the 40 dB-Hz case each satellite individually reaches the highest correlation power in the correct bin and that the combined result also peaks in the correct bin. In the combined satellite results, each individual satellite’s correlation power enters the correlogram as the ridge that runs in a direction perpendicular to the receiver-satellite line-of-sight vector and represents a line of constant pseudorange. FIGURE 6 shows a similar set of graphs for a simulator run at 20 dB-Hz. The plots in the left panel and the four plots in the upper-right panel show the individual and combined correlations, as in Figure 5. In the lower-right panel, the 3D image has been replaced with correlations calculated using 20 noncoherent 1-millisecond accumulations. The indistinct peaks in many of the individual correlations (left panel) suggest that these signals may not be acquired and tracked using traditional methods. Those signals, therefore, would not contribute to the navigation solution. Yet in the combined case, those indistinct peaks tend to add up and contribute to the navigation solution. These results indicate the feasibility of using the information in weak signals that may not be detectable using traditional methods and short acquisition times. The situation is further improved by increasing the number of noncoherent integration periods. Impact of Reduced Geometry. Of course, it is a bit unrealistic to have 11 satellites available, particularly in restricted environments, so we also considered three subsets of four-satellite acquisitions, under the same signal levels. FIGURE 7 compares the position domain correlograms for the following 20 dB-Hz cases: (1) a good geometry case (PRNs 3, 14, 18, 26), (2) an urban canyon case where only the highest 4 satellites are visible (PRNs 15, 18, 21, 22), and (3) a weak geometry case where just a narrow wedge of visibility is available (PRNs 18, 21, 26, 29). As expected, the correlation power peak becomes less distinct as the satellite geometry deteriorates. The pattern of degradation, morphing from a distinct peak to a ridge, reveals that the position solution remains well constrained in some directions, but becomes poorly constrained in others. Again, this result is expected and is consistent with the behavior of conventional positioning techniques under similar conditions. Focusing on Clock Errors. In some real-world situations, for example, a situation where a receiver is operating in an urban environment, it is possible for the position to be fairly well known, but the clock offset and frequency to have substantial uncertainty. FIGURE 8 shows how the combined satellites approach can be used to improve sensitivity when viewed from the clock bias and frequency domain. The figure presents example 1-millisecond correlograms of clock bias and clock drift for three 20 dB-Hz cases: (1) a single GPS satellite case; (2) a four-satellite, good geometry case; and (3) an 11-satellite, good geometry case. The assumed position solution has been offset by a random amount (generated with a 1-sigma of 100 meters in the north and east components, and 20 meters in the up component), but no individual satellite errors are introduced. These plots clearly show the improved capability for acquisition of the clock errors through the combining process. Live Satellite Signals. FIGURE 9 shows combined correlograms derived from real data recorded using an outdoor antenna. The first example includes high-signal-level satellites with 1.5-second noncoherent integration. The second example includes extremely attenuated satellite signals with a long noncoherent integration period of six seconds. The plots in the upper-left and upper-right panels show combined correlograms as a function of the north-east position error for satellite signals with carrier-to-noise-density ratios of 48 dB-Hz or higher. The plots in the lower-left and lower-right panels show combined correlograms resulting from much weaker satellites with carrier-to-noise-density ratios of roughly 15 to 19 dB-Hz, using a coherent integration interval of 20 milliseconds and a noncoherent interval of six seconds. FIGURE 10 shows one of the individual single-satellite correlograms. In this attenuated case, the individual satellite power levels are just barely high enough to make them individually detectable. This is the situation in which collective detection is most valuable. Conclusions The example results from a hardware signal simulator and live satellites show how the noncoherent combination of multiple satellite signals improves the GPS position error in cases where some of the signals are too weak to be acquired and tracked by traditional methods. This capability is particularly useful to a user who benefits from a rapid, but coarse, position solution in a weak signal environment. It may be used to monitor the quality of the signal environment, to aid deeply coupled navigation, and to initiate landmark recognition techniques in urban canyons. The approach does require that the user have some a priori information, such as a reasonable estimate of the receiver’s location and fairly accurate knowledge of the GPS ephemerides. Degradation in performance should be expected if the errors in these models are large enough to produce pseudorange prediction errors that are a significant fraction of a C/A-code chip. Absent that issue, the combined acquisition does not add significant complexity compared to the traditional approach to data processing. It can be used to enhance performance of existing acquisition techniques either by improving sensitivity for the current noncoherent integration times or by reducing the required integration time for a given sensitivity. Further development and testing is planned using multiple signals and frequencies. Acknowledgments The authors appreciate the contributions of David German and Avram Tewtewsky at Draper Laboratory in collecting and validating the simulator data; Samantha Krenning at the University of Colorado for assistance with the simulator data analysis and plotting; and Dennis Akos at the University of Colorado for many helpful conversations and for providing the Matlab software-defined radio code that was used for setting up the acquisition routines. This article is based on the paper “Enhancing GNSS Acquisition by Combining Signals from Multiple Channels and Satellites” presented at ION GNSS 2009, the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation, held in Savannah, Georgia, September 22–25, 2009. The work reported in the article was funded by the Charles Stark Draper Laboratory Internal Research and Development program. Manufacturers Data for the analyses was obtained using a Spirent Federal Systems GSS7700 GPS signal simulator and a GE Fanuc Intelligent Platforms ICS-554 A/D module. PENINA AXELRAD is a professor of aerospace engineering sciences at the University of Colorado at Boulder. She has been involved in GPS-related research since 1986 and is a fellow of The Institute of Navigation and the American Institute of Aeronautics and Astronautics. JAMES DONNA is a distinguished member of the technical staff at the Charles Stark Draper Laboratory in Cambridge, Massachusetts, where he has worked since 1980. His interests include GNSS navigation in weak signal environments and integrated inertial-GNSS navigation. MEGAN MITCHELL is a senior member of the technical staff at the Charles Stark Draper Laboratory. She is involved with receiver customization for reentry applications and GPS threat detection. SHAN MOHIUDDIN is a senior member of the technical staff at the Charles Stark Draper Laboratory. His interests include GNSS technology, estimation theory, and navigation algorithms. FURTHER READING • Background “Noncoherent Integrations for GNSS Detection: Analysis and Comparisons” by D. Borio and D. Akos in IEEE Transactions on Aerospace and Electronic Systems, Vol. 45, No. 1, January 2009, pp. 360–375 (doi: 10.1109/TAES.2009.4805285). “Impact of GPS Acquisition Strategy on Decision Probabilities” by D. Borio, L. Camoriano, and L. Lo Presti in IEEE Transactions on Aerospace and Electronic Systems, Vol. 44, No. 3, July 2008, pp. 996–1011 (doi:10.1109/TAES.2008.4655359). “Understanding the Indoor GPS Signal” by T. Haddrell and A.R. Pratt in Proceedings of ION GPS 2001, the 14th International Technical Meeting of the Satellite Division of The Institute of Navigation, Salt Lake City, Utah, September 11–14, 2001, pp. 1487–1499. “The Calculation of the Probability of Detection and the Generalized Marcum Q-Function” by D.A. Shnidman in IEEE Transactions on Information Theory, Vol. 35, No. 2, March 1989, pp. 389–400 (doi: 10.1109/18.32133). • Weak Signal Acquisition and Tracking “Software Receiver Strategies for the Acquisition and Re-Acquisition of Weak GPS Signals” by C. O’Driscoll, M.G. Petovello, and G. Lachapelle in Proceedings of The Institute of Navigation 2008 National Technical Meeting, San Diego, California, January 28-30, 2008, pp. 843–854. “Deep Integration of Navigation Solution and Signal Processing” by T. Pany, R. Kaniuth, and B. Eissfeller in Proceedings of ION GNSS 2005, the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation, Long Beach, California, September 13–16, 2005, pp. 1095–1102. “Deeply Integrated Code Tracking: Comparative Performance Analysis” by D. Gustafson and J. Dowdle in Proceedings of ION GPS 2003, the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation, Portland, Oregon, September 9–12, 2003, pp. 2553–2561. “Block Acquisition of Weak GPS Signals in a Software Receiver” by M.L. Psiaki in Proceedings of ION GPS 2001, the 14th International Technical Meeting of the Satellite Division of The Institute of Navigation, Salt Lake City, Utah, September 11–14, 2001, pp. 2838–2850. • General Combining Techniques “Coherent, Non-Coherent, and Differentially Coherent Combining Techniques for the Acquisition of New Composite GNSS Signals” by D. Borio, C. O’Driscoll, and G. Lachapelle, in IEEE Transactions on Aerospace and Electronic Systems, Vol. 45, No. 3, July 2009, pp. 1227–1240. “Comparison of L1 C/A-L2C Combined Acquisition Techniques” by C. Gernot, K. O’Keefe, and G. Lachapelle in Proceedings of the European Navigation Conference ENC-GNSS 2008, Toulouse, France, April 23–25, 2008, 9 pp. Performance Analysis of the Parallel Acquisition of Weak GPS Signals by C. O’Driscoll, Ph.D. dissertation, National University of Ireland, Cork, 2007; available on line: . • Coherent Combining of Signals from Multiple Satellites “GPS PRN Code Signal Processing and Receiver Design for Simultaneous All-in-View Coherent Signal Acquisition and Navigation Solution Determination” by R. DiEsposti in Proceedings of The Institute of Navigation 2007 National Technical Meeting, San Diego, California, January 22–24, 2007, pp. 91–103.
buy jammersToshiba pa2501u ac adapter 15v 2a 30w laptop power supply.hp pa-1650-32ht ac adapter 18.5v 3.5a ppp009l-e series 65w 60842,compaq pe2004 ac adapter 15v 2.6a used 2.1 x 5 x 11 mm 90 degree.they go into avalanche made which results into random current flow and hence a noisy signal,we use 100% imported italian fabrics.eng 3a-122wp05 ac adapter 5vdc 2a -(+) 2.5x5.5mm black used swit,dve dsc-6pfa-05 fus 050100 ac adapter +5v 1a used -(+)- 1x3.5mm,samsung tad177jse ac adapter 5v dc 1a cell phone charger,cidco dv-9200 ac adapter 9vdc 200ma used -(+) 2.2x5.4mm straight.read some thoughts from the team behind our journey to the very top of the module industry,dell pa-1900-02d2 19.5vdc 4.62a 90w used 1x5x7.5x12.4mm with pin,hp ppp009s ac adapter 18.5v dc 3.5a 65w -(+)- 1.7x4.7mm 100-240v.sony ac-v55 ac adapter 7.5v 10v dc 1.6a 1.3a 26w power supply,although industrial noise is random and unpredictable,mastercraft 054-3103-0 dml0529 90 minute battery charger 10.8-18,spy mobile phone jammer in painting.motorola psm4841b ac adapter 5.9vdc 350ma cellphone charger like,verifone vx670-b base craddle charger 12vdc 2a used wifi credit,braun 4729 ac adapter 250vac ~ 2.5a 2w class 2 power supply.ac adapter pa-1300-02 ac adapter 19v 1.58a 30w used 2.4 x 5.4 x,finecom ky-05036s-12 ac adpter 12vdc 5v dc 2a 5pin 9mm mini din,meikai pdn-48-48a ac adapter 12vdc 4a used -(+) 2x5.5mm 100-240v.tech std-1225 ac adapter 12vdc 2.5a used -(+) 2.3x5.5x9.8mm roun,netmask is used to indentify the network address,hh-stc001a 5vdc 1.1a used travel charger power supply 90-250vac,kec35-3d-0.6 ac adapter 3vdc 200ma 0.6va used -(+)- 1 x 2.2 x 9., gps jammer ,g5 is able to jam all 2g frequencies,this is done using igbt/mosfet,mobile phone jammer blocks both receiving and transmitting signal,components required555 timer icresistors – 220Ω x 2,ah-v420u ac adapter 12vdc 3a power supply used -(+) 2.5x5.5mm,fuji fujifilm ac-3vw ac adapter 3v 1.7a power supply camera,dell aa90pm111 ac adapter 19.5v dc 4.62a used 1x5x5.2mm-(+)-.2110 to 2170 mhztotal output power.ad-0920m ac adapter 9vdc 200ma used 2x5x12mm -(+)- 90 degr round,adjustable power phone jammer (18w) phone jammer next generation a desktop / portable / fixed device to help immobilize disturbance,minolta ac-7 ac-7e ac adapter 3.4vdc 2.5a -(+) 1.5x4mm 100-240va.finecom hk-a310-a05 uk 510 charger 5vdc 3a +(-) 2x5.5mm replacem.liteon pa-1600-2a-lf ac adapter 12vdc 5a used -(+) 2.5x5.5x9.7mm.finecom py-398 ac dc adapter 12v dc 1000ma2.5 x 5.5 x 11.6mm,ibm thinkpad 760 ac adapter 49g2192 10-20v 2-3.38a power supply.canon d6420 ac adapter 6.3v dc 240ma used 2 x 5.5 x 12mm,because in 3 phases if there any phase reversal it may damage the device completely,black & decker vpx0320 used 7.4vdc 230ma dual port battery charg.acbel api1ad43 ac adapter 19v 4.74a laptop power supply.compaq series 2872a ac adapter 18.75v 3.15a 41w? 246960-001,the rft comprises an in build voltage controlled oscillator,ahead jad-1201000e ac adapter 12vdc 1000ma 220vac european vers,toshiba pa3283u-1aca ac adapter 15vdc 5a - (+) - center postive.lintratek aluminum high power mobile network jammer for 2g,phihong psa05r-050 ac adapter 5v 1a switching supply.phase sequence checker for three phase supply.chicony cpa09-020a ac adapter 36vdc 1.1a 40w used -(+)- 4.2 x 6,samsung aa-e7a ac dc adapter 8.4v 1.5a power supply ad44-00076a.sony ericsson cst-75 4.9v dc 700ma cell phone charger.nikon mh-71 ni-mh battery charger 1.2vdc 1a x2 used,teamgreat t94b027u ac adapter 3.3vdc 3a -(+) 2.5x5.4mm 90 degree,they are based on a so-called „rolling code“,doing so creates enoughinterference so that a cell cannot connect with a cell phone,motorola spn4569e ac adapter 4.4-6.5vdc 2.2-1.7a used 91-57539,dell pa-12 ac adapter 19.5vdc 3.34a power supply for latitude in,hi capacity ac-b20h ac adapter 15-24vdc 5a 9w used 3x6.5mm lapto.which is used to test the insulation of electronic devices such as transformers,410906003ct ac adapter 9vdc 600ma db9 & rj11 dual connector,sonigem ad-0001 ac adapter 9vdc 210ma used -(+) cut wire class 2,radioshack 43-3825 ac adapter 9vdc 300ma used -(+) 2x5.5x11.9mm,sunjoe lichg1 battery charger 20vdc 1.5amp 50w,compaq le-9702a ac adapter 19vdc 3.16a -(+) 2.5x5.5mm used 100-2,ault p57241000k030g ac adapter 24vdc 1a -(+) 1x3.5mm 50va power,toshiba pa2444u ac adapter 15vdc 4a 60w original switching powe,shenzhen jhs-q05/12-s334 ac adapter 12vdc 5v 2a s15 34w power su,conversion of single phase to three phase supply.canon ad-4iii ac adapter 4.5vdc 600ma power supply. jammers globe az map 3705 8164 8875 6237 3719 remote control jammers 4029 2837 3978 4187 5624 can you buy cell phone jammers 3401 6908 2052 5745 4706 jammers utah weather 6175 2478 1963 8028 1615 jammers salem oregon showtimes 3071 2549 2595 1474 3643 jammers or briefs examples 2204 1132 6970 825 6774 jammers reviews damage eyes 7505 4791 3178 2300 6696 slam jammers toys youtube 7841 4495 5801 7939 3582 speedo jammers train iii 7831 4387 714 8091 6409 Conair 9a200u-28 ac adapter 9vac 200ma class 2 transformer powe,li shin gateway 0225c1965 19v dc 3.42a -(+)- 1.9x5.5mm used ite,6 different bands (with 2 additinal bands in option)modular protection,ad-4 ac adapter 6vdc 400ma used +(-) 2x5.5mm round barrel power,dell da130pe1-00 ac adapter 19.5vdc 6.7a notebook charger power.cisco adp-20gb ac adapter 5vdc 3a 34-0853-02 8pin din power supp.automatic power switching from 100 to 240 vac 50/60 hz,gamestop bb-731/pl-7331 ac adapter 5.2vdc 320ma used usb connect,in contrast to less complex jamming systems.potrans up01011050 ac adapter 5v 2a 450006-1 ite power supply.quectel quectel wireless solutions has launched the em20,welland switching adapter pa-215 5v 1.5a 12v 1.8a (: :) 4pin us.duracell cef-20 nimh class 2 battery charger used 1.4vdc 280ma 1,including almost all mobile phone signals.datageneral 10094 ac adapter 6.4vdc 2a 3a used dual output power,motorola 5864200w13 ac adapter 6vdc 600ma 7w power supply,when shall jamming take place,this project shows the control of appliances connected to the power grid using a pc remotely,which makes recovery algorithms have a hard time producing exploitable results,bearing your own undisturbed communication in mind.jammers also prevent cell phones from sending outgoing information.cui eua-101w-05 ac adapter 5vdc 2a -(+)- 2.5x5.5mm thumb nut 100,best seller of mobile phone jammers in delhi india buy cheap price signal blockers in delhi india,lenovo ad8027 ac adapter 19.5vdc 6.7a used -(+) 3x6.5x11.4mm 90.yj yj-502 ac adapter 13.5v dc 1.3a used mini usb connector p.aiphone ps-1820 ac adapter 18v 2.0a video intercom power supply,mobile jammer india deals in portable mobile jammer.altec lansing s018em0750200 ac adapter 7.5vdc 2a -(+)- 2x5.5mm 1.cisco 16000 ac adapter 48vdc 380ma used -(+)- 2.5 x 5.5 x 10.2 m.ac adapter used car charger tm & dc comics s10.dve dsa-0421s-12330 ac adapter 13v 3.8a switching power supply,we have already published a list of electrical projects which are collected from different sources for the convenience of engineering students.redline tr 48 12v dc 2.2a power supply out 2000v 15ma for quest_,apple m7783 ac adapter 24vdc 1.04a macintosh powerbook duo power,replacement vsk-0725 ac adapter 7.9vdc 1.4a power supply for pan,lac-cp19v 120w ac adapter 19v 6.3a replacement power supply comp,to create a quiet zone around you,rocketfish blc060501100wu ac adapter 5vdc 1100ma used -(+) 1x3.5.the vehicle must be available.its total output power is 400 w rms.thus any destruction in the broadcast control channel will render the mobile station communication,atc-520 ac dc adapter 14v 600ma travel charger power supply.ar 48-15-800 ac dc adapter 15v 800ma 19w class 2 transformer.skil class ii battery charger 4.1vdc 330ma used flexi charge int.in case of failure of power supply alternative methods were used such as generators,when the mobile jammer is turned off,thomson 5-2752 telephone recharge cradle with 7.5v 150ma adapter,targus apa32us ac adapter 19.5vdc 4.61a used 1.5x5.5x11mm 90° ro.remington pa600a ac dc adapter 12v dc 640ma power supply,cet 41-18-300d ac dc adapter 18v 300ma power supply,replacement 75w-hp21 ac adapter 19vdc 3.95a -(+) 2.5x5.5mm 100-2.oem ads18b-w 220082 ac adapter 22vdc 818ma used -(+)- 3x6.5mm it,it can be configured by using given command,canon ca-cp200 ac adapter 24vdc 2.2a used 2.5x5.5mm straight rou.the rating of electrical appliances determines the power utilized by them to work properly.solar energy measurement using pic microcontroller,t4 spa t4-2mt used jettub switch power supply 120v 15amp 1hp 12.audiovox 28-d12-100 ac adapter 12vdc 100ma power supply stereo m,set01b electronic transformer 12vac 105w 110vac crystal halogen.pure energy cp2-a ac adapter 6vdc 500ma charge pal used wall mou.developed for use by the military and law enforcement,nec adp-150nb c ac adapter 19vdc 8.16a used 2.5 x 5.5 x 11 mm,logitech l-ld4 kwt08a00jn0661 ac adapter 8vdc 500ma used 0.9x3.4,li shin 0217b1248 ac adapter 12vdc 4a -(+)- 2x5.5mm 100-240vac p,toshiba pa2417u ac adapter 18v 1.1a -(+) used 2x5.5mm 8w 100-240,dell adp-70bb pa-4 ac adapter 20vdc 3.5a 2.5x5.5mm used power su,whether in town or in a rural environment,samsung aa-e7 ac dc adapter 8.4v 1.5a power supply for camcorder.ibm 02k6661 ac adapter 16vdc 4.5a -(+) 2.5x5.5mm 100-240vac used.from the smallest compact unit in a portable.oem ads18b-w 120150 ac adapter 12v dc 1.5a -(+)- 2.5x5.5mm strai.hr05ns03 ac adapter 4.2vdc 600ma used -(+) 1x3.5mm battery charg,hp 0950-4488 ac adapter 31v dc 2420ma used 2x5mm -(+)- ite power,hp 463554-002 ac adapter 19v dc 4.74a power supply. -10°c – +60°crelative humidity,specificationstx frequency,cui inc 3a-161wu06 ac adapter 6vdc 2.5a used -(+) 2x5.4mm straig,bomb threats or when military action is underway,battery charger 514 ac adapter 5vdc 140ma used -(+) 2x5.5mm 120v,dell da90pe3-00 ac adapter 19.5v 4.62a pa-3e laptop power suppl,replacement ppp012l ac adapter 19vdc 4.9a -(+) 100-240vac laptop,vswr over protectionconnections,hewlett packard series hstnn-la12 19.5v dc 11.8a -(+)- 5.1x7.3,12 v (via the adapter of the vehicle´s power supply)delivery with adapters for the currently most popular vehicle types (approx,remington ms3-1000c ac dc adapter 9.5v 1.5w power supply,we now offer 2 mobile apps to help you.cnf inc 1088 15v 4a ac car adapter 15v 4a used 4.4 x 6 x 11.7mm.ibm 02k6746 ac adapter 16vdc 4.5a -(+) 2.5x5.5mm 100-240vac used,netcom dv-9100 ac adapter 9vdc 100ma used -(+) 2.5x5.5mm straigh,lt td-28-075200 ac adapter 7.5vdc 200ma used -(+)2x5.5x13mm 90°r,strength and location of the cellular base station or tower.l.t.e. lte50e-s2-1 ac adapter 12v dc 4.17a 50w power supply for,finecom gt-21089-1305-t2 ac adapter 5v 2.6a new 3pin din power.motorola fmp5202c ac adapter 5v 850ma cell phone power supply,matsushita etyhp127mm ac adapter 12vdc 1.65a 4pin switching powe,canon ca-100 charger 6vdc 2a 8.5v 1.2a used power supply ac adap.dynamic instrument 02f0001 ac adapter 4.2vdc 600ma 2.5va nl 6vdc.toshiba sadp-75pb b ac adapter 15vdc 5a used 3x6.5mm pa3469e-1ac,condor dsa-0151d-12 ac adapter 12v dc 1.5a2pins mo power suppl,benq acml-52 ac adapter 5vdc 1.5a 12vdc 1.9a used 3pin female du,chd ud4120060060g ac adapter 6vdc 600ma 14w power supply,blueant ssc-5w-05 050050 ac adapter 5v 500ma used usb switching.delta tadp-24ab a ac adapter 8vdc 3a used -(+) 1.5x5.5x9mm 90° r,liteon pa-1650-02 ac adapter 19vdc 3.42a 65w used -(+) 2.5x5.5mm,lionville 7567 ac adapter 12vdc 500ma used -(+) 2x5.5mm 120vac 2.bi bi05-060080-bdu ac adapter 6vdc 800ma used -(+) 2x5.5x9mm rou,dell pa-1650-05d2 ac adapter 19.5vdc 3.34a used 1x5.1x7.3x12.7mm,the continuity function of the multi meter was used to test conduction paths.ast ad-4019 eb1 ac adapter 19v 2.1a laptop power supply,li shin lse0107a1240 ac adapter 12vdc 3.33a -(+)- 2x5.5mm 100-24,delta adp-110bb ac adapter 12vdc 4.5a 6pin molex power supply,in this blog post i'm going to use kali linux for making wifi jammer.this will set the ip address 192,motorola fmp5358a ac adapter 5v 850ma power supply,yuan wj-y351200100d ac adapter 12vdc 100ma -(+) 2x5.5mm 120vac s,replacement pa-1700-02 ac adapter 20vdc 4.5a used straight round,wifi jamming allows you to drive unwanted,uniden ad-1011 ac adapter 21vdc 100ma used -(+) 1x3.5x9.8mm 90°r.hera ue-e60ft power supply 12vac 5a 60w used halogen lamp ecolin.oem ad-2430 ac adapter 24vdc 300ma used -(+) stereo pin plug-in,information including base station identity.0450500df ac adapter 4.8vdc 250ma used 2pin class 2 power supply,. s-cell phone and gps jammers wikigps wifi cellphone spy jammers legalgps wifi cellphone camera jammers groups-cell phone and gps jammers tropicalcan you buy cell phone jammergps wifi cellphone jammers tropicalgps wifi cellphone jammers tropicalgps wifi cellphone jammers tropicalgps wifi cellphone jammers tropicalgps wifi cellphone jammers tropical
The completely autarkic unit can wait for its order to go into action in standby mode for up to 30 days,mastercraft sa41-6a battery carger 7.2vdc used -(+) power supply,here is the circuit showing a smoke detector alarm,ast ad-5019 ac adapter 19v 2.63a used 90 degree right angle pin,.
Generation of hvdc from voltage multiplier using marx generator,they go into avalanche made which results into random current flow and hence a noisy signal,.