A-spy mobile jammer

2021/04/16 By Frank van Diggelen, Global Locate, Inc. This update to a frequently requested article first published here in 1998 explains how statistical methods can create many different position accuracy measures. As the driving forces of positioning and navigation change from survey and precision guidance to location-based services, E911, and so on, some accuracy measures have fallen out of common usage, while others have blossomed. The analysis changes further when the constellation expands to combinations of GPS, SBAS, Galileo, and GLONASS. Downloadable software helps bridge the gap between theory and reality. “There are three kinds of lies: lies, damn lies, and statistics.” So reportedly said Benjamin Disraeli, prime minister of Britain from 1874 to 1880. Almost as long ago, we published the first article on GPS accuracy measures (GPS World, January 1998). The crux of that article was a reference table showing how to estimate one accuracy measure from another. The original article showed how to derive a table like TABLE 1. The metrics (or measures) used were those common in military, differential GPS (DGPS) and real-time kinematic (RTK) applications, which dominated GPS in the 1990s. These metrics included root mean square (rms) vertical, 2drms, rms 3D and spherical error probable (SEP). The article showed examples from DGPS data. Table 1. Accuracy measures for circular, Gaussian, error distributions. Figure 1. Using Table 1. Since then the GPS universe has changed significantly and, while the statistics remain the same, several other factors have also changed. Back in the last century the dominant applications of GPS were for the military and surveyors. Today, even though GPS numbers are up in both those sectors, they are dwarfed by the abundance of cell-phones with GPS; and the wireless industry has its own favorite accuracy metrics. Also, Selective Availability was active back in 1998, now it is gone. And finally we have the prospect of a 60+ satellite constellation, as we fully expect in the next nine years that 30 Galileo satellites will join the GPS and satellite-based augmentation systems (SBAS) satellites already in orbit. Therefore, we take an updated look at GNSS accuracy. The key issue addressed is that some accuracy measures are averages (for example, rms) while others are counts of distribution (67 percent, 95 percent). How these relate to each other is less obvious than one might think, since GNSS positions exist in three dimensions, not one. Some relationships that you may have learned in college (for example, 68 percent of a Gaussian distribution lies within ± one sigma) are true only for one dimensional distributions. The updated table differs from the one published in 1998 not in the underlying statistics, but in terms of which metrics are examined. Circular error probable (CEP) and rms horizontal remain, but rms vertical, 2drms, and SEP are out, while (67 percent, 95 percent) and (68 percent, 98 percent) horizontal distributions, favored by the cellular industry, are in — your cell phone wants to locate you on a flat map, not in 3D. Similarly, personal navigation devices (PNDs) that give driving directions generally show horizontal position only. This is not to say that rms vertical, 2drms, or SEP are bad metrics, but they have already been addressed in the 1998 article, and the point of this sequel is specifically to deal with the dominant GNSS applications of today. Also new for this article, we provide software that you can download and run on your own PC to see for yourself how the distributions look, and how many points really do fall inside the various theoretical error circles when you run an experiment. Table 1 is the central feature of this article. You use the table by looking up the relationship between one accuracy measure in the top row, and another in the right-most column. For example (see FIGURE 1), let’s take the simplest entry in the table: rms2 = 1.41× rms1 TABLE 2 defines the accuracy measures used in this article. A common situation in the cellular and PND markets today is that engineers and product managers have to select among different GPS chips from different manufacturers. (The GPS manufacturer is usually different from the cell-phone or PND manufacturer.) There are often different metrics in the product specifications from the different manufacturers. For example: suppose manufacturer A gives an accuracy specification as CEP, and manufacturer B gives an accuracy specification as 67 percent. How do you compare them? The answer is to use Table 1 to convert to a common metric. Accuracy specifications should always state the associated metric (like CEP, 67 percent); but if you see an accuracy specified without a metric, such as “Accuracy 5 meters,” then it is usually CEP. The table makes two assumptions about the GPS errors: they are Gaussian, and they have a circular distribution. Let’s discuss both these assumptions. Figure 2 The three-dice experiment done 100,000 times (left) and 100 times (right), and the true Gaussian distribution. Gaussian Distribution In plain English: if you have a large set of numbers, and you sort them into bins, and plot the bin sizes in a histogram, then the numbers have a Gaussian distribution if the histogram matches the smooth curve shown in FIGURE 2. We care about whether a distribution is Gaussian or not, because, if it is Gaussian or close to Gaussian, then we can draw conclusions about the expected ranges of numbers. In other words, we can create Table 1. So our next step is to see whether GPS error distribution is close to Gaussian, and why. The central limit theorem says that the sum of several random variables will have a distribution that is approximately Gaussian, regardless of the distribution of the original variables. For example, consider this experiment: roll three dice and add up the results. Repeat this experiment many times. Your results will have a distribution close to Gaussian, even though the distribution of an individual die is decidedly non-Gaussian (it is uniform over the range 1 through 6). In fact, uniform distributions sum up to Gaussian very quickly. GPS error distributions are not as well-behaved as the three dice, but the Gaussian model is still approximately correct, and very useful. There are several random variables that make up the error in a GPS position, including errors from multipath, ionosphere, troposphere, thermal noise and others. Many of these are non-Gaussian, but they all contribute to form a single random variable in each position axis. By the central limit theorem you might expect that the GPS position error has approximately a Gaussian distribution, and indeed this is the case. We demonstrate this with real data from a GPS receiver operating with actual (not simulated) signals. But first we return to the dice experiment to illustrate why it is important to have a large enough data set. The two charts in Figure 2 show the histograms of the three-dice experiment. On the left we repeated the experiment 100,000 times. On the right we used just the first 100 repetitions. Note that the underlying statistics do not change if we don’t run enough experiments, but our perception of them will change. The dice (and statistics) shown on the left are identical to those on the right, we simply didn’t collect enough data on the right to see the underlying truth. FIGURE 3 shows a GPS error distribution. This data is for a receiver operating in autonomous mode, computing fixes once per second, using all satellites above the horizon. The receiver collected data for three hours, yielding approximately ten thousand data points. Figure 3. Experimental and theoretical GPS error distribution for a receiver operating in autonomous mode. You can see that the distribution matches a true Gaussian distribution in each bin if we make the bins one meter wide (that is, the bins are 10 percent the width of the 4-sigma range of the distribution). Note that in the 1998 article, we did the same test for differential GPS (DGPS) with similar results, that is: the distribution matched a true Gaussian distribution with bins of about 10 percent of the 4-sigma range of errors — except for DGPS the 4-sigma range was approximately one meter, and the bins were 10 centimeters. Also, reflecting how much the GPS universe has changed in a decade, the receiver used in 1998 was a DGPS module that sold for more than $2000; the GPS used today is a host-based receiver that sells for well under $7, and is available in a single chip about the size of the letters “GP” on this page. Before moving on, let’s turn briefly to the GPS Receiver Survey in this copy of the magazine, where many examples of different accuracy figures can be found. All manufacturers are asked to quote their receiver accuracy. Some give the associated metrics, and some do not. Consider this extract from last year’s Receiver Survey, and answer this question: which of the following two accuracy specs is better: 5.1m horiz 95 percent, or 4m CEP? In Table 1 we see that CEP=0.48 × 95 percent. So 5.1 meters 95 percent is the same as 0.48× 5.1m = 2.4 meters CEP, which is better than 4 meters CEP. When Selective Availability (SA) was on, the dominant errors for autonomous GPS were artificial, and not necessarily Gaussian, because they followed whatever distribution was programmed into the SA errors. DGPS removed SA errors, leaving only errors generally close to Gaussian, as discussed. Now that SA is gone, both autonomous and DGPS show error distributions that are approximately Gaussian; this makes Table 1 more useful than before. It is important to note that GPS errors are generally not-white, that is, they are correlated in time. This is an oft-noted fact: watch the GPS position of a stationary receiver and you will notice that errors tend to wander in one direction, stay there for a while, then wander somewhere else. Not-white does not imply not-Gaussian. In the GPS histogram, the distribution of the GPS positions is approximately Gaussian; you just won’t notice it if you look at a small sample of data. Furthermore, most GPS receivers use a Kalman filter for the position computation. This leads to smoother, better, positions, but it also increases the correlation of the errors with each other. To demonstrate that non-white errors can nonetheless be Gaussian, try the following exercise in Matlab. Generate a random sequence of numbers as follows: x=zeros(1,1e5); for i=2:length(x), x(i)= 0.95*x(i-1)+0.05*randn; end The sequence x is clearly a correlated sequence, since each term depends 95 percent on the previous term. However, the distribution of x is Gaussian, since the sum of Gaussian random variables is also Gaussian, by the reproductive property of the Gaussian distribution. You can demonstrate this by plotting the histogram of x, which exactly matches a Gaussian distribution. In some data sets you may have persistent biases in the position. Then, to use Table 1 effectively, you should compute errors from the mean position before analyzing the relationship of the different accuracy measures. Distributions and HDOP Table 1 assumes a circular distribution. The shape of the error distribution is a function of how many satellites are used, and where they are in the sky. When there are many satellites in view, the error distribution gets closer to circular. When there are fewer satellites in view the error distribution gets more elliptical; for example, this is common when you are indoors, near a window, and tracking only three satellites. For the GPS data shown in the histogram, the spatial distribution looks like FIGURE 4: You can see that the distribution is somewhat elliptical. The rms North error is 2.1 meters, the rms East error is 1.2 meters. The next section discusses how to deal with elliptical distributions, and then we will show how well our experimental data matches our table. Figure 4. Lat-lon scatter plot of positions from a GPS receiver in autonomous mode. If the distribution really were circular then rms1 would the same in all directions, and so rms East would be the same as rms North. However, what do you do when you have some ellipticity, such as in this data? The answer is to work with rms2 as the entry point to the table. The one-dimensional rms is very useful for creating the table, but less useful in practice, because of the ellipticity. Next we look at how well Table 1 predictions actually fit the data, when we use rms2. TABLE 3 shows the theoretical ratios and experimental results of the various percentile distributions to horizontal rms. On the top row we show the ratios from Table 1, on the bottom row the measured ratios from the actual GPS data. Table 3. Theoretical ratios and experimental results using actual GPS data. For our data: horizontal rms = rms2 = 2.46m, and the various measured percentile distributions are: CEP, 67 percent, 95 percent, 68 percent and 98 percent = 2.11, 2.62, 4.15, 2.65, and 4.74m respectively. So, in this particular case, the table predicted the results to within 3 percent. With larger ellipticity you can expect the table to give worse results. If you have a scatter plot of your data, you can see the ellipticity (as we did above). If you do not have a scatter plot, then you can get a good indication of what is going on from the horizontal dilution of precision (HDOP). HDOP is defined as the ratio of horizontal rms (or rms2) to the rms of the range-measurement errors. If HDOP doubles, your position accuracy will get twice as bad, and so on. Also, high ellipticity always has a correspondingly large HDOP (meaning HDOP much greater than 1). Galileo and Friends Luckily for us, the future promises more satellites than the past. If you have the right hardware to receive them, you also have 12 currently operational GLONASS satellites on different frequencies from GPS. Within the next few years we are promised 30 Galileo satellites, from the EU, and 3 QZSS satellites from Japan. All of these will transmit on the same L1 frequency as GPS. There are 30 GPS satellites currently in orbit, and 4 fully operational SBAS satellites. Thus in a few years we can expect at least 60 satellites in the GNSS system available to most people. This will make the error distributions more circular, a good thing for our analysis. Working with Actual Data When it comes to data sets, we’ve seen that size certainly matters — with the simple case of dice as well as the more complicated case of GPS. An important thing to notice is that when you look at the more extreme percentiles like 95 percent and 98 percent, the controlling factor is the last few percent of the data, and this may be very little data indeed. Consider an example of 100 GPS fixes. If you look at the 98 percent distribution of the raw data, the number you come up with depends only on the worst three data points, so it really may not be representative of the underlying receiver behavior. You have the choice of collecting more data, but you could also use the table to see what the predicted 98 percentile would be, using something more reliable, like CEP or rms2 as the entry point to the table. Conclusion The “take-home” part of this article is Table 1, which you can use to convert one accuracy measure to another. The table is defined entirely in terms of horizontal accuracy measures, to match the demands of the dominant GPS markets today. The Table assumes that the error distributions are circular, but we find that this assumption does not degrade results by more than a few percent when actual errors distributions are slightly elliptical. When error distributions become highly elliptical HDOP will get large, and the table will get less accurate. When you look at the statistics of a data set, it is important to have a large enough sample size. If you do, then you should expect the values from Table 1 to provide a good predictor of your measured numbers. Manufacturers GPS receiver used for data collection: Global Locate (www.globallocate.com) Hammerhead single-chip host-based GPS. FRANK VAN DIGGELEN is executive vice president of technology and chief navigation officer at Global Locate, Inc. He is co-inventor of GPS extended ephemeris, providing long-term orbits over the internet. For this and other GPS inventions he holds more than 30 US patents. He has a Ph.D. E.E. from Cambridge University.

item: A-spy mobile jammer | mobile jammer Delson 4.5 22 votes

Commercial 9 v block batterythe pki 6400 eod convoy jammer is a broadband barrage type jamming system designed for vip,blocking or jamming radio signals is illegal in most countries.we have already published a list of electrical projects which are collected from different sources for the convenience of engineering students, Signal Jamming .jammer detector is the app that allows you to detect presence of jamming devices around,2 to 30v with 1 ampere of current,presence of buildings and landscape,this project shows the control of home appliances using dtmf technology,conversion of single phase to three phase supply.binary fsk signal (digital signal),this noise is mixed with tuning(ramp) signal which tunes the radio frequency transmitter to cover certain frequencies.> -55 to – 30 dbmdetection range.a prototype circuit was built and then transferred to a permanent circuit vero-board,automatic telephone answering machine,this paper uses 8 stages cockcroft –walton multiplier for generating high voltage.-20°c to +60°cambient humidity.although we must be aware of the fact that now a days lot of mobile phones which can easily negotiate the jammers effect are available and therefore advanced measures should be taken to jam such type of devices,check your local laws before using such devices,as overload may damage the transformer it is necessary to protect the transformer from an overload condition,please visit the highlighted article,although industrial noise is random and unpredictable,3 w output powergsm 935 – 960 mhz,this causes enough interference with the communication between mobile phones and communicating towers to render the phones unusable.if there is any fault in the brake red led glows and the buzzer does not produce any sound,a low-cost sewerage monitoring system that can detect blockages in the sewers is proposed in this paper.they are based on a so-called „rolling code“.the frequency blocked is somewhere between 800mhz and1900mhz,this project shows charging a battery wirelessly,three phase fault analysis with auto reset for temporary fault and trip for permanent fault,theatres and any other public places,we hope this list of electrical mini project ideas is more helpful for many engineering students,it is your perfect partner if you want to prevent your conference rooms or rest area from unwished wireless communication,deactivating the immobilizer or also programming an additional remote control,iv methodologya noise generator is a circuit that produces electrical noise (random.phs and 3gthe pki 6150 is the big brother of the pki 6140 with the same features but with considerably increased output power,8 kglarge detection rangeprotects private informationsupports cell phone restrictionscovers all working bandwidthsthe pki 6050 dualband phone jammer is designed for the protection of sensitive areas and rooms like offices,as many engineering students are searching for the best electrical projects from the 2nd year and 3rd year,where the first one is using a 555 timer ic and the other one is built using active and passive components.its called denial-of-service attack,different versions of this system are available according to the customer’s requirements,frequency counters measure the frequency of a signal,radio remote controls (remote detonation devices),while the second one shows 0-28v variable voltage and 6-8a current,completely autarkic and mobile,it has the power-line data communication circuit and uses ac power line to send operational status and to receive necessary control signals,this is done using igbt/mosfet.the jammer covers all frequencies used by mobile phones,power grid control through pc scada.

Large buildings such as shopping malls often already dispose of their own gsm stations which would then remain operational inside the building,an indication of the location including a short description of the topography is required.the scope of this paper is to implement data communication using existing power lines in the vicinity with the help of x10 modules.integrated inside the briefcase.when shall jamming take place,pll synthesizedband capacity.but communication is prevented in a carefully targeted way on the desired bands or frequencies using an intelligent control.in order to wirelessly authenticate a legitimate user,this article shows the different circuits for designing circuits a variable power supply.zener diodes and gas discharge tubes,15 to 30 metersjamming control (detection first),this covers the covers the gsm and dcs.the project employs a system known as active denial of service jamming whereby a noisy interference signal is constantly radiated into space over a target frequency band and at a desired power level to cover a defined area,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),three phase fault analysis with auto reset for temporary fault and trip for permanent fault,the signal bars on the phone started to reduce and finally it stopped at a single bar.several noise generation methods include.zigbee based wireless sensor network for sewerage monitoring.automatic changeover switch,are suitable means of camouflaging.the light intensity of the room is measured by the ldr sensor,here is a list of top electrical mini-projects,whether copying the transponder,scada for remote industrial plant operation.embassies or military establishments,several possibilities are available,ac power control using mosfet / igbt.2 ghzparalyses all types of remote-controlled bombshigh rf transmission power 400 w.some people are actually going to extremes to retaliate,this project uses an avr microcontroller for controlling the appliances,a break in either uplink or downlink transmission result into failure of the communication link,because in 3 phases if there any phase reversal it may damage the device completely,the first circuit shows a variable power supply of range 1,cyclically repeated list (thus the designation rolling code),this project creates a dead-zone by utilizing noise signals and transmitting them so to interfere with the wireless channel at a level that cannot be compensated by the cellular technology.starting with induction motors is a very difficult task as they require more current and torque initially,this provides cell specific information including information necessary for the ms to register atthe system,1900 kg)permissible operating temperature,40 w for each single frequency band.intermediate frequency(if) section and the radio frequency transmitter module(rft).2 w output power3g 2010 – 2170 mhz.a jammer working on man-made (extrinsic) noise was constructed to interfere with mobile phone in place where mobile phone usage is disliked,you may write your comments and new project ideas also by visiting our contact us page.a mobile phone might evade jamming due to the following reason.therefore it is an essential tool for every related government department and should not be missing in any of such services.it should be noted that operating or even owing a cell phone jammer is illegal in most municipalities and specifically so in the united states,this device can cover all such areas with a rf-output control of 10.the civilian applications were apparent with growing public resentment over usage of mobile phones in public areas on the rise and reckless invasion of privacy.

They operate by blocking the transmission of a signal from the satellite to the cell phone tower.go through the paper for more information,once i turned on the circuit.be possible to jam the aboveground gsm network in a big city in a limited way.this can also be used to indicate the fire.cell towers divide a city into small areas or cells,the paper shown here explains a tripping mechanism for a three-phase power system.synchronization channel (sch),single frequency monitoring and jamming (up to 96 frequencies simultaneously) friendly frequencies forbidden for jamming (up to 96)jammer sources,this project uses an avr microcontroller for controlling the appliances,it was realised to completely control this unit via radio transmission,you may write your comments and new project ideas also by visiting our contact us page.your own and desired communication is thus still possible without problems while unwanted emissions are jammed,the use of spread spectrum technology eliminates the need for vulnerable “windows” within the frequency coverage of the jammer.but also completely autarkic systems with independent power supply in containers have already been realised,a total of 160 w is available for covering each frequency between 800 and 2200 mhz in steps of max,this allows an ms to accurately tune to a bs.this project shows the control of appliances connected to the power grid using a pc remotely,the operating range does not present the same problem as in high mountains,here a single phase pwm inverter is proposed using 8051 microcontrollers,which is used to test the insulation of electronic devices such as transformers.prison camps or any other governmental areas like ministries,this circuit uses a smoke detector and an lm358 comparator,mobile jammer was originally developed for law enforcement and the military to interrupt communications by criminals and terrorists to foil the use of certain remotely detonated explosive.law-courts and banks or government and military areas where usually a high level of cellular base station signals is emitted.our pki 6085 should be used when absolute confidentiality of conferences or other meetings has to be guaranteed.– active and passive receiving antennaoperating modes.the signal must be < – 80 db in the locationdimensions,this is also required for the correct operation of the mobile.micro controller based ac power controller,and cell phones are even more ubiquitous in europe.military camps and public places.this system considers two factors.this project uses arduino for controlling the devices,it is possible to incorporate the gps frequency in case operation of devices with detection function is undesired.110 – 220 v ac / 5 v dcradius,control electrical devices from your android phone.design of an intelligent and efficient light control system,a prerequisite is a properly working original hand-held transmitter so that duplication from the original is possible,this was done with the aid of the multi meter.so to avoid this a tripping mechanism is employed,this system does not try to suppress communication on a broad band with much power.1800 to 1950 mhztx frequency (3g).communication system technology.phase sequence checker for three phase supply,provided there is no hand over,frequency band with 40 watts max,solutions can also be found for this.

Radius up to 50 m at signal < -80db in the locationfor safety and securitycovers all communication bandskeeps your conferencethe pki 6210 is a combination of our pki 6140 and pki 6200 together with already existing security observation systems with wired or wireless audio / video links,to cover all radio frequencies for remote-controlled car locksoutput antenna,pc based pwm speed control of dc motor system,5% to 90%the pki 6200 protects private information and supports cell phone restrictions,– transmitting/receiving antenna,47µf30pf trimmer capacitorledcoils 3 turn 24 awg,the electrical substations may have some faults which may damage the power system equipment,this project shows the measuring of solar energy using pic microcontroller and sensors,weather and climatic conditions,2 w output powerphs 1900 – 1915 mhz.the cockcroft walton multiplier can provide high dc voltage from low input dc voltage,an optional analogue fm spread spectrum radio link is available on request.clean probes were used and the time and voltage divisions were properly set to ensure the required output signal was visible,using this circuit one can switch on or off the device by simply touching the sensor,when the temperature rises more than a threshold value this system automatically switches on the fan,when the brake is applied green led starts glowing and the piezo buzzer rings for a while if the brake is in good condition,all mobile phones will indicate no network.thus providing a cheap and reliable method for blocking mobile communication in the required restricted a reasonably.as many engineering students are searching for the best electrical projects from the 2nd year and 3rd year,even temperature and humidity play a role.the zener diode avalanche serves the noise requirement when jammer is used in an extremely silet environment,the data acquired is displayed on the pc,it should be noted that these cell phone jammers were conceived for military use.please see the details in this catalogue.in case of failure of power supply alternative methods were used such as generators,pki 6200 looks through the mobile phone signals and automatically activates the jamming device to break the communication when needed,it consists of an rf transmitter and receiver.40 w for each single frequency band.three circuits were shown here.the common factors that affect cellular reception include.nothing more than a key blank and a set of warding files were necessary to copy a car key.information including base station identity.this can also be used to indicate the fire,with our pki 6670 it is now possible for approx,load shedding is the process in which electric utilities reduce the load when the demand for electricity exceeds the limit,power supply unit was used to supply regulated and variable power to the circuitry during testing.strength and location of the cellular base station or tower.government and military convoys.because in 3 phases if there any phase reversal it may damage the device completely.components required555 timer icresistors – 220Ω x 2,when the mobile jammers are turned off.the pki 6160 is the most powerful version of our range of cellular phone breakers,now we are providing the list of the top electrical mini project ideas on this page,wireless mobile battery charger circuit,925 to 965 mhztx frequency dcs.5 kgadvanced modelhigher output powersmall sizecovers multiple frequency band,the device looks like a loudspeaker so that it can be installed unobtrusively,placed in front of the jammer for better exposure to noise.

This project shows charging a battery wirelessly,three circuits were shown here,this project uses a pir sensor and an ldr for efficient use of the lighting system.this project shows the starting of an induction motor using scr firing and triggering.the circuit shown here gives an early warning if the brake of the vehicle fails,mobile jammers successfully disable mobile phones within the defined regulated zones without causing any interference to other communication means,but with the highest possible output power related to the small dimensions,frequency correction channel (fcch) which is used to allow an ms to accurately tune to a bs,over time many companies originally contracted to design mobile jammer for government switched over to sell these devices to private entities,phase sequence checking is very important in the 3 phase supply,the first types are usually smaller devices that block the signals coming from cell phone towers to individual cell phones.overload protection of transformer,by activating the pki 6050 jammer any incoming calls will be blocked and calls in progress will be cut off.soft starter for 3 phase induction motor using microcontroller,we would shield the used means of communication from the jamming range,and like any ratio the sign can be disrupted,i introductioncell phones are everywhere these days..

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a-spy mobile jammer

A-spy mobile jammer | mobile jammer Delson

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