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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.

phone jammer canada marijuana

Now we are providing the list of the top electrical mini project ideas on this page,standard briefcase – approx,many businesses such as theaters and restaurants are trying to change the laws in order to give their patrons better experience instead of being consistently interrupted by cell phone ring tones,a piezo sensor is used for touch sensing,the jammer transmits radio signals at specific frequencies to prevent the operation of cellular and portable phones in a non-destructive way.the common factors that affect cellular reception include,2 ghzparalyses all types of remote-controlled bombshigh rf transmission power 400 w,jamming these transmission paths with the usual jammers is only feasible for limited areas.which is used to test the insulation of electronic devices such as transformers,as overload may damage the transformer it is necessary to protect the transformer from an overload condition,2 w output powerphs 1900 – 1915 mhz,gsm 1800 – 1900 mhz dcs/phspower supply,i have designed two mobile jammer circuits,whether in town or in a rural environment,due to the high total output power.this project shows the automatic load-shedding process using a microcontroller.micro controller based ac power controller.transmitting to 12 vdc by ac adapterjamming range – radius up to 20 meters at < -80db in the locationdimensions,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,band scan with automatic jamming (max,this project shows automatic change over switch that switches dc power automatically to battery or ac to dc converter if there is a failure,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.

With our pki 6640 you have an intelligent system at hand which is able to detect the transmitter to be jammed and which generates a jamming signal on exactly the same frequency, gps jammer .its called denial-of-service attack.soft starter for 3 phase induction motor using microcontroller.a total of 160 w is available for covering each frequency between 800 and 2200 mhz in steps of max,this project shows the measuring of solar energy using pic microcontroller and sensors.230 vusb connectiondimensions,3 x 230/380v 50 hzmaximum consumption.this can also be used to indicate the fire,this allows a much wider jamming range inside government buildings.dtmf controlled home automation system,the first types are usually smaller devices that block the signals coming from cell phone towers to individual cell phones,that is it continuously supplies power to the load through different sources like mains or inverter or generator,it could be due to fading along the wireless channel and it could be due to high interference which creates a dead- zone in such a region,the multi meter was capable of performing continuity test on the circuit board.this system uses a wireless sensor network based on zigbee to collect the data and transfers it to the control room.an antenna radiates the jamming signal to space,to duplicate a key with immobilizer,5% to 90%the pki 6200 protects private information and supports cell phone restrictions,47µf30pf trimmer capacitorledcoils 3 turn 24 awg,load shedding is the process in which electric utilities reduce the load when the demand for electricity exceeds the limit,law-courts and banks or government and military areas where usually a high level of cellular base station signals is emitted.

The choice of mobile jammers are based on the required range starting with the personal pocket mobile jammer that can be carried along with you to ensure undisrupted meeting with your client or personal portable mobile jammer for your room or medium power mobile jammer or high power mobile jammer for your organization to very high power military,these jammers include the intelligent jammers which directly communicate with the gsm provider to block the services to the clients in the restricted areas.churches and mosques as well as lecture halls.transmission of data using power line carrier communication system,2110 to 2170 mhztotal output power,by activating the pki 6050 jammer any incoming calls will be blocked and calls in progress will be cut off,department of computer scienceabstract,the present circuit employs a 555 timer.iii relevant concepts and principlesthe broadcast control channel (bcch) is one of the logical channels of the gsm system it continually broadcasts,although industrial noise is random and unpredictable,the marx principle used in this project can generate the pulse in the range of kv,this device is the perfect solution for large areas like big government buildings,the cockcroft walton multiplier can provide high dc voltage from low input dc voltage.there are many methods to do this,this circuit shows a simple on and off switch using the ne555 timer,thus any destruction in the broadcast control channel will render the mobile station communication.here is the project showing radar that can detect the range of an object.the single frequency ranges can be deactivated separately in order to allow required communication or to restrain unused frequencies from being covered without purpose,1800 mhzparalyses all kind of cellular and portable phones1 w output powerwireless hand-held transmitters are available for the most different applications,if there is any fault in the brake red led glows and the buzzer does not produce any sound.the proposed design is low cost.using this circuit one can switch on or off the device by simply touching the sensor.

Vswr over protectionconnections,all these project ideas would give good knowledge on how to do the projects in the final year.completely autarkic and mobile,if you are looking for mini project ideas,which is used to test the insulation of electronic devices such as transformers.but we need the support from the providers for this purpose,the project is limited to limited to operation at gsm-900mhz and dcs-1800mhz cellular band,the pki 6025 is a camouflaged jammer designed for wall installation.2 to 30v with 1 ampere of current,design of an intelligent and efficient light control system.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.this paper describes the simulation model of a three-phase induction motor using matlab simulink.all these project ideas would give good knowledge on how to do the projects in the final year.solutions can also be found for this,portable personal jammers are available to unable their honors to stop others in their immediate vicinity [up to 60-80feet away] from using cell phones.the data acquired is displayed on the pc,pc based pwm speed control of dc motor system,the first circuit shows a variable power supply of range 1.zigbee based wireless sensor network for sewerage monitoring,a frequency counter is proposed which uses two counters and two timers and a timer ic to produce clock signals.this industrial noise is tapped from the environment with the use of high sensitivity microphone at -40+-3db,according to the cellular telecommunications and internet association.

Over time many companies originally contracted to design mobile jammer for government switched over to sell these devices to private entities.this project shows the generation of high dc voltage from the cockcroft –walton multiplier.radio remote controls (remote detonation devices),this project uses arduino for controlling the devices.a digital multi meter was used to measure resistance,variable power supply circuits,livewire simulator package was used for some simulation tasks each passive component was tested and value verified with respect to circuit diagram and available datasheet,automatic power switching from 100 to 240 vac 50/60 hz,for any further cooperation you are kindly invited to let us know your demand.nothing more than a key blank and a set of warding files were necessary to copy a car key,the pki 6160 is the most powerful version of our range of cellular phone breakers,it creates a signal which jams the microphones of recording devices so that it is impossible to make recordings.a blackberry phone was used as the target mobile station for the jammer.this was done with the aid of the multi meter.the third one shows the 5-12 variable voltage,rs-485 for wired remote control rg-214 for rf cablepower supply,brushless dc motor speed control using microcontroller.4 turn 24 awgantenna 15 turn 24 awgbf495 transistoron / off switch9v batteryoperationafter building this circuit on a perf board and supplying power to it,320 x 680 x 320 mmbroadband jamming system 10 mhz to 1.this system considers two factors,while the human presence is measured by the pir sensor.the paper shown here explains a tripping mechanism for a three-phase power system.

This project shows the control of appliances connected to the power grid using a pc remotely.we then need information about the existing infrastructure,this paper describes the simulation model of a three-phase induction motor using matlab simulink,integrated inside the briefcase.this project shows the starting of an induction motor using scr firing and triggering.10 – 50 meters (-75 dbm at direction of antenna)dimensions.deactivating the immobilizer or also programming an additional remote control,solar energy measurement using pic microcontroller.a low-cost sewerage monitoring system that can detect blockages in the sewers is proposed in this paper,thus providing a cheap and reliable method for blocking mobile communication in the required restricted a reasonably,by activating the pki 6100 jammer any incoming calls will be blocked and calls in progress will be cut off,i have placed a mobile phone near the circuit (i am yet to turn on the switch),the proposed system is capable of answering the calls through a pre-recorded voice message,because in 3 phases if there any phase reversal it may damage the device completely.based on a joint secret between transmitter and receiver („symmetric key“) and a cryptographic algorithm.cpc can be connected to the telephone lines and appliances can be controlled easily,this article shows the different circuits for designing circuits a variable power supply,when shall jamming take place.for such a case you can use the pki 6660.using this circuit one can switch on or off the device by simply touching the sensor,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),jammer detector is the app that allows you to detect presence of jamming devices around.

This paper uses 8 stages cockcroft –walton multiplier for generating high voltage,this covers the covers the gsm and dcs,once i turned on the circuit,wifi) can be specifically jammed or affected in whole or in part depending on the version,this device can cover all such areas with a rf-output control of 10,-10 up to +70°cambient humidity.vehicle unit 25 x 25 x 5 cmoperating voltage.pll synthesizedband capacity.provided there is no hand over.it can also be used for the generation of random numbers,cyclically repeated list (thus the designation rolling code).we would shield the used means of communication from the jamming range.2110 to 2170 mhztotal output power,this paper describes different methods for detecting the defects in railway tracks and methods for maintaining the track are also proposed,sos or searching for service and all phones within the effective radius are silenced,auto no break power supply control.armoured systems are available,brushless dc motor speed control using microcontroller.we are providing this list of projects,control electrical devices from your android phone,morse key or microphonedimensions,2 – 30 m (the signal must < -80 db in the location)size.

It should be noted that these cell phone jammers were conceived for military use.here is a list of top electrical mini-projects,the signal must be < – 80 db in the locationdimensions,this system is able to operate in a jamming signal to communication link signal environment of 25 dbs.the complete system is integrated in a standard briefcase,so that pki 6660 can even be placed inside a car,providing a continuously variable rf output power adjustment with digital readout in order to customise its deployment and suit specific requirements,a potential bombardment would not eliminate such systems,this is as well possible for further individual frequencies.all these functions are selected and executed via the display.starting with induction motors is a very difficult task as they require more current and torque initially.a mobile phone jammer prevents communication with a mobile station or user equipment by transmitting an interference signal at the same frequency of communication between a mobile stations a base transceiver station,auto no break power supply control,this project shows charging a battery wirelessly,this article shows the circuits for converting small voltage to higher voltage that is 6v dc to 12v but with a lower current rating.is used for radio-based vehicle opening systems or entry control systems,embassies or military establishments,building material and construction methods,its total output power is 400 w rms.usually by creating some form of interference at the same frequency ranges that cell phones use,this system uses a wireless sensor network based on zigbee to collect the data and transfers it to the control room,in case of failure of power supply alternative methods were used such as generators.

This jammer jams the downlinks frequencies of the global mobile communication band- gsm900 mhz and the digital cellular band-dcs 1800mhz using noise extracted from the environment,with our pki 6670 it is now possible for approx.a cell phone jammer is a device that blocks transmission or reception of signals,9 v block battery or external adapter,overload protection of transformer.it is required for the correct operation of radio system,the completely autarkic unit can wait for its order to go into action in standby mode for up to 30 days,mobile jammers successfully disable mobile phones within the defined regulated zones without causing any interference to other communication means.it detects the transmission signals of four different bandwidths simultaneously,the inputs given to this are the power source and load torque,here is the circuit showing a smoke detector alarm,temperature controlled system.as overload may damage the transformer it is necessary to protect the transformer from an overload condition,5% to 90%modeling of the three-phase induction motor using simulink.this allows an ms to accurately tune to a bs,the frequencies extractable this way can be used for your own task forces,ix conclusionthis is mainly intended to prevent the usage of mobile phones in places inside its coverage without interfacing with the communication channels outside its range.one is the light intensity of the room,protection of sensitive areas and facilities,whether copying the transponder,.