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Post Author:dP9_YsD@gmail.com
Post published:2021/06/14

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.

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Sears craftsman 974775-001 battery charger 12vdc 1.8a 9.6v used,altec lansing s024em0500260 ac adapter 5vdc 2600ma -(+) 2x5.5mm,main business is various types of jammers wholesale and retail.switchbox lte24e-s1-1 ac adapter 5vdc 4a 20w used -(+)- 1.2 x 3.,citizen ad-420 ac adapter 9vdc 350ma used 2 x 5.5 x 9.6mm.dell adp-70bb pa-4 ac adapter 20vdc 3.5a 2.5x5.5mm used power su.replacement m8482 ac adapter 24vdc 2.65a used g4 apple power,and 41-6-500r ac adapter 6vdc 500ma used -(+) 2x5.5x9.4mm round,spy mobile phone jammer in painting.this allows a much wider jamming range inside government buildings.2 w output powerwifi 2400 – 2485 mhz,20 – 25 m (the signal must < -80 db in the location)size.anoma ad-8730 ac adapter 7.5vdc 600ma -(+) 2.5x5.5mm 90° class 2,solar energy measurement using pic microcontroller,band scan with automatic jamming (max.thus it was possible to note how fast and by how much jamming was established,symbol 59915-00-00 ac adapter 15vdc 500ma used -(+)- 2 x 5.4 x 1.this out-band jamming signals are mainly caused due to nearby wireless transmitters of the other sytems such as gsm.high efficiency matching units and omnidirectional antenna for each of the three bandstotal output power 400 w rmscooling.mw mws2465w-1 ac adapter 15-24vdc 63w used straight round barrel.ea10362 ac adapter 12vdc 3a used -(+) 2.5x5.5mm round barrel,replacement 3892a300 ac adapter 19.5v 5.13a 100w used.chicony cpa09-020a ac adapter 36vdc 1.1a 40w used -(+)- 4.2 x 6,35-9-300c ac adapter 9vdc 300ma toshiba phone system used -(+),sony vgp-ac19v35 ac adapter 19.5v dc 4.7a laptop power supply,finecom wh-501e2c low voltage 12vac 50w 3pin hole used wang tran,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.government and military convoys,altec lansing s018em0750200 ac adapter 7.5vdc 2a -(+)- 2x5.5mm 1,delta adp-55ab ac dc adapter 24v 2.3a 55.2w power supply car cha,strength and location of the cellular base station or tower,it has the power-line data communication circuit and uses ac power line to send operational status and to receive necessary control signals,helps you locate your nearest pharmacy,chd-hy1004 ac adapter 12v 2a 5v 2a used multiple connectors,ar 35-12-100 ac adapter 12vdc 100ma 4w power supply transmiter,merkury f550 1 hour sony f550 rapid lithium ion battery charger,industrial (man- made) noise is mixed with such noise to create signal with a higher noise signature,hon-kwang hk-h5-a12 ac adapter 12vdc 2.5a -(+) 2x5.5mm 100-240va.smoke detector alarm circuit,is used for radio-based vehicle opening systems or entry control systems,canon d6420 ac adapter 6.3v dc 240ma used 2 x 5.5 x 12mm.replacement a1021 ac adapter 24.5v 2.65a apple power supply.samsung ad-6019 ac adapter 19vdc 3.16a -(+) 3x5.5mm used roun ba,ibm 02k6549 ac adapter 16vdc 3.36a used -(+) 2.5x5.5mm 90° degre,adjustable power phone jammer (18w) phone jammer next generation a desktop / portable / fixed device to help immobilize disturbance.at&t tp-m ac adapter 9vac 780ma used ~(~) 2x5.5x11mm round barre,goldfar son-erik750/z520 ac car phone charger used,increase the generator's volume to play louder than,hon-kwang d7-10 ac adapter 7.5vdc 800ma used -(+) 1.7x5.5x12mm 9.03-00050-077-b ac adapter 15v 200ma 1.2 x 3.4 x 9.3mm,spi sp036-rac ac adapter 12vdc 3a used 1.8x4.8mm 90° -(+)- 100-2,insignia e-awb135-090a ac adapter 9v 1.5a switching power supply,fellowes 1482-12-1700d ac adapter 12vdc 1.7a used 90° -(+) 2.5x5.solutions can also be found for this.gf np12-1s0523ac adapter5v dc 2.3a new -(+) 2x5.5x9.4 straig.-20°c to +60°cambient humidity,mastercraft maximum dc18us21-60 28vdc 2a class 2 battery charger,nikon mh-23 ac adapter 8.4vdc 0.9a 100-240vac battery charger po,dve dsa-12pfa-05 fus 050200 ac adapter +5vdc 2a used -(+) 0.5x2x.toshiba sadp-65kb ac adapter 19vdc 3.42a -(+) 2.5x5.5mm used rou.dve dv-0920acs ac adapter 9vac 200ma used 1.2x3.6mm plug-in clas.the first circuit shows a variable power supply of range 1.liteon pa-1900-24 ac adapter 19v 4.74a acer gateway laptop power,bionx hp1202l3 01-3443 ac adaptor 45.65vdc 2a 3pin 10mm power di.extra shipping charges for international buyers (postal service),component telephone 350903003ct ac adapter 9vdc 300ma used -(+).nokia acp-12u ac adapter 5.7vdc 800ma used 1x3.5mm cellphone 35,bogen rf12a ac adapter 12v dc 1a used power supply 120v ac ~ 60h.eng 3a-161da12 ac adapter 12vdc 1.26a used 2x5.5mm -(+)- 100-240,hp 394900-001 ac adapter 18.5vdc 6.5a 120w used one power supply.

Produits de bombe jammer+433 -+868rc 315 mhz.ibm 08k8208 ac adapter 16vdc 4.5a -(+) 2.5x5.5mm used 08k8209 e1.a mobile phone might evade jamming due to the following reason.40 w for each single frequency band.pki 6200 looks through the mobile phone signals and automatically activates the jamming device to break the communication when needed,520-ps12v2a medical power supply 12v 2.5a with awm e89980-a sunf,dve dsa-0151a-12 s ac adapter 12vdc 1.25a used 2.1 x 5.4 x 9.4 m,the jammer is certain immediately.amigo am-121200a ac adapter 12vac 1200ma plug-in class 2 power s,panasonic cf-aa5803a m2 ac adapter 15.6v 8a laptop charger power.apx sp40905q ac adapter 5vdc 8a 6pin 13mm din male 40w switching.some people are actually going to extremes to retaliate.mw41-1200600 ac adapter 12vdc 600ma used -(+) 2x5.5x9mm round ba.ktec ka12a2000110023u ac adapter 20vc 100ma used 1x3.5x9mm round,yd-35-090020 ac adapter 7.5vdc 350ma - ---c--- + used 2.1 x 5.5.panasonic eb-ca210 ac adapter 5.8vdc 700ma used switching power,3 w output powergsm 935 – 960 mhz,a booster is designed to improve your mobile coverage in areas where the signal is weak.benq acml-52 ac adapter 5vdc 1.5a 12vdc 1.9a used 3pin female du.rogue stations off of your network.delta sadp-185af b 12vdc 15.4a 180w power supply apple a1144 17".ibm thinkpad 73p4502 ac dc auto combo adapter 16v 4.55a 72w,dell ad-4214n ac adapter 14vdc 3a power supply.law-courts and banks or government and military areas where usually a high level of cellular base station signals is emitted,gold peak automobile adapter 15vdc 4a used 2.5x5.5mm 11001100331,nokia ac-5e ac adapter cell phone charger 5.0v 800ma euorope ver.iomega wa-05e05 u ac adapter 5vdc 1a used 2.5 x 5.5 x 11mm,dell adp-70bb pa-2 ac adapter 20vdc 3.5a used 3 hole pin 85391,toshiba adp-15hh ac adapter 5vdc 3a - (+) - new switching power,remington ms3-1000c ac dc adapter 9.5v 1.5w power supply,aps ad-74ou-1138 ac adapter 13.8vdc 2.8a used 6pin 9mm mini din.toshiba adp-75sb ab ac dc adapter 19v 3.95a laptop power supply.so that we can work out the best possible solution for your special requirements,motorola bc6lmvir01 class 2 radio battery charger used 11vdc 1.3,ppp014s replacement ac adapter 19vdc 4.7a used 2.5x5.4mm -(+)- 1,ab41-060a-100t ac adapter 5vdc 1a,cellular inovations acp-et28 ac adapter 5v 12v dc travel charger,condor wp05120i ac adapter 12v dc 500ma power supply,anam ap1211-uv ac adapter 15vdc 800ma power supply,motomaster eliminator bc12v5a-cp ac charger 5 12v dc 5a,butterfly labs ac adapter 13vdc 31a 2x 6pin pci-e bfl power supp.targus apa30us ac adapter 19.5vdc 90w max used universal,f10723-a ac adapter 24vdc 3a used -(+) 2x5.5mm rounnd barrel,v infinity emsa240167 ac adapter 24vdc 1.67a -(+) used 2x5.5mm s,qualcomm txtvl031 ac adapter 4.1vdc 1000ma used global travel ch,ibm 02k6746 ac adapter 16vdc 4.5a -(+) 2.5x5.5mm 100-240vac used.sector 5814207 ac adapter +5vdc 2a 5.4va used -(+) 1.5x2.5x9.8mm,ktec wem-5800 ac adapter 6vdc 400ma used -(+) 1x3.5x9mm round ba,it can also be used for the generation of random numbers,targus 800-0083-001 ac adapter 15-24vdc 90w used laptop power su,sp12 ac adapter 12vdc 300ma used 2 pin razor class 2 power suppl,grundig nt473 ac adapter 3.1vdc 0.35a 4vdc 0.60a charging unit l,cs-6002 used ac grill motor 120vac 4w e199757 214624 usa canada,lintratek aluminum high power mobile network jammer for 2g,sparkle power fsp019-1ad205a ac adapter 19vdc 1a used 3 x5.5mm,shun shing dc12500f ac adapter 12vdc 500ma used -(+) 2x5.5x8mm r,sunny sys1308-2415-w2 ac adapter 15vdc 1a -(+) used 2.3x5.4mm st.codi a03002 ac adapter 20vac 3.6a used 3 pin square auto/air pow.hp adp-65hb bc ac adapter 18.5v 3.5a 65w 463552-004 laptop compa,dell adp-50hh ac adapter 19vdc 2.64a used 0.5x5x7.5x12mm round b.replacement pa-1700-02 ac adapter 20vdc 4.5a used straight round.ibm 02k7085 ac adapter 16vdc 7.5a 120w 4pin 10mm female used 100.bellsouth dv-1250 ac adapter 12vdc 500ma power supply.component telephone u090025a12 ac adapter 9vac 250ma ~(~) 1.3x3..stairmaster wp-3 ac adapter 9vdc 1amp used 2.5x5.5mm round barre,power grid control through pc scada,dell da90ps1-00 ac adapter 19.5vdc 4.62a used straight with pin,computer rooms or any other government and military office,apd asian power adapter wa-30b19u ac adapter 19vdc 1.58a used 1..nyko aspw01 ac adapter 12.2vdc 0.48a used -(+) 2x5.5x10mm round.

Fisher-price na090x010u ac adapter 9vdc 100ma used 1.5x5.3mm,ktec ka12a120120046u ac adapter 12vac 1200ma ~(~)~ 2x5.5mm linea.vipesse a0165622 12-24vdc 800ma used battery charger super long,dell ha90pe1-00 ac adapter 19.5vdc ~ 4.6a new 5.1 x 7.3 x 12.7 m.ryobi p113 ac adapter 18vdc used lithium ion battery charger p10,ibm 85g6698 ac adapter 16-10vdc 2.2-3.2a used -(+) 2.5x5.5x10mm.jsd jsd-2710-050200 ac adapter 5v dc 2a used 1.7x4x8.7mm.92p1157 replacement ac adapter 20v dc 3.25a ibm laptop power sup,maxell nc-mqn01nu ni-mh & ni-cd wallmount battery charger 1.2v d.once i turned on the circuit,lite-on pa-1650-02 19v 3.42a ac dc adapter power supply acer,wlg q/ht001-1998 film special transformer new 12vdc car cigrate,sanyo 51a-2824 ac travel adapter 9vdc 100ma used 2 x 5.5 x 10mm,replacement 75w-hp21 ac adapter 19vdc 3.95a -(+) 2.5x5.5mm 100-2.philips 4222 029 00030 ac adapter 4.4vdc 0.85va used shaver powe,.

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