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Photo: peeterv/iStock/Getty Images Plus/Getty Images Ambiguity and Environmental Data: Two Further Key Challenges of Multisensor Positioning By Paul D. Groves, Lei Wang, Debbie Walter, and Ziyi Jiang, University College London The coming requirements of greater accuracy and reliability in a range of challenging environments for a multitude of mission-critical applications require a multisensor approach and an over-arching methodology that does not yet exist. Part 1 of this article, in the October issue, examined the two key concepts of complexity and context. In this continuation, we complete our overview with exploration of the requirements of ambiguity and environmental data. Ambiguity occurs when measurements can be interpreted in more than one way, leading to different navigation solutions, only one of which is correct. Any navigation technique can potentially produce ambiguous measurements. The likelihood depends on both the positioning method and the context, both environmental and behavioral. Urban and indoor positioning techniques that do not require dedicated infrastructure are particularly vulnerable to ambiguity. Poor handling of ambiguity results in erroneous navigation solutions and the navigation system can become “lost,” whereby it is unable to recover and may even reject correct measurements. There are six main causes of ambiguity: feature identification, pattern matching, propagation anomalies, geometry, system reliability, and context ambiguity. Each of these is described in turn below. Feature Identification Ambiguity. The proximity, ranging, angular positioning, and Doppler positioning methods all use landmarks for positioning. These may be radio, acoustic, or optical signals, or natural or man-made features of the environment. For reliable positioning, these signals or features must be correctly identified. Digital signals intended for positioning incorporate identification codes. However, where a signal is weak and/or interference is high, it may be possible to use the signal for positioning but not decode the identification information. For signals of opportunity — that is, not designed for positioning — the identification codes may be encrypted, while analog signals do not typically have identifiers. These signals must be identified using their frequencies and an approximate user position, in which case there may be multiple candidates. Even where a signal of opportunity is identifiable, the transmission site may change without warning. For example, Wi-Fi access points are sometimes moved and mobile phone networks are periodically refigured. Thus, there is a risk of false landmark identification. Environmental features are difficult to identify uniquely. In image-based navigation, man-made features, such as roads, buildings, and signs, are easiest to identify in images due to their line and corner features. However, similar objects are often repeated in relatively close proximity. For example, Figure 18 shows the locations of the five “no entry” signs in a 1,200-meter circuit of Central London streets. Two of the signs are within 20 meters of each other. (Figure numbering continues the sequence beginning in Part 1, October issue.) Figure 18. “No entry” signs in a 1,200-meter circuit of Central London. (Background image courtesy of Bing maps | Photo: Paul D. Groves, Lei Wang, Debbie Walter and Ziyi Jiang, University College London) Pattern-Matching Ambiguity. The pattern-matching positioning method maintains a database of measurable parameters that vary with position. Examples include terrain height, magnetic field variations, Wi-Fi signal strengths, and GNSS signal availability information. Values measured at the current unknown user position are compared with predictions from the database over a series of candidate positions. The position solution is then obtained from the highest scoring candidate(s). An inherent characteristic of pattern matching is that there is sometimes a good match between measurements and predictions at more than one candidate position. Figure 19 and Figure 20 show GNSS shadow-matching scoring maps based on smartphone measurements taken at the same location 40 seconds apart. The scores are obtained by comparing GNSS signal-to-noise measurements with signal availability predictions derived from a 3D city model. In Figure 19, maximum scores (shown in dark red) are only obtained in the correct street, whereas in Figure 20, there is also a high-scoring area in the adjacent street, giving two possible position solutions. Figure 19. GNSS shadow-matching scoring map – unambiguous case (the cross shows the true position and white areas are indoor locations). (Photo: Paul D. Groves, Lei Wang, Debbie Walter and Ziyi Jiang, University College London) Figure 20. GNSS shadow-matching scoring map – unambiguous case (the cross shows the true position and white areas are indoor locations). (Photo: Paul D. Groves, Lei Wang, Debbie Walter and Ziyi Jiang, University College London) Figure 21 presents another example, showing the height of a road vehicle derived from a barometric altimeter at three different times. Provided the altimeter is regularly calibrated, it may be used for terrain-referenced navigation (TRN), determining the car’s position along the road by comparing the measured height with a database. However, if only the current height is compared, it will typically match the database at multiple locations within the search area, as the figure shows. The ambiguity can be reduced by comparing a series of measurements from successive epochs, known as a transect, with the database. This approach is applicable to any pattern-matching technique. However, increasing the transect length to reduce the ambiguity also reduces the update rate, and the ambiguity problem can never be eliminated completely. Figure 21. Height of a car derived from a barometric altimeter at three different times; readings of around 235 m are highlighted. (Photo: Paul D. Groves, Lei Wang, Debbie Walter and Ziyi Jiang, University College London) Signal Propagation Anomalies. The ranging, angular positioning, and Doppler positioning methods all make the assumption that the signal propagates from the transmitter (or other landmark) to the user in a straight line at constant speed. Significant position errors can therefore arise when these assumptions are not valid due to phenomena such as non-line-of-sight reception, multipath interference, and severe atmospheric refraction. In challenging environments, such as dense urban areas and indoors, multiple signals are typically affected by propagation anomalies, and it is not always easy to determine which signals are contaminated. Where the position solution is overdetermined (that is, more than the minimum number of signals are received), different combinations of signals will produce different position solutions when there are significant propagation anomalies.  Figures 22 and 23 illustrate this for conventional GNSS positioning using a Leica Viva geodetic receiver, showing the position errors obtained using different combinations of GPS and GLONASS signals. In Figure 22, the receiver is located on a high rooftop and the majority of position solutions are within 15 meters of the mean, with the remainder easily dismissible as outliers. However, in Figure 23, where the receiver is located in a dense urban location, the candidate position solutions are spread over more than 100 meters, and the correct position solution is not clear. The densest cluster of positions is far from both the centroid and the truth. Therefore, anomalous signal propagation may be treated as an ambiguity problem. Figure 22. GNSS position errors using different combinations of signals in a rooftop environment. (Photo: Paul D. Groves, Lei Wang, Debbie Walter and Ziyi Jiang, University College London) Figure 23. GNSS position errors using different combinations of signals in a dense urban environment. (Photo: Paul D. Groves, Lei Wang, Debbie Walter and Ziyi Jiang, University College London) Geometric Ambiguity. Geometric ambiguity occurs when more than one position solution may be derived from a set of otherwise unambiguous measurements. Figure 24 shows two examples. On the left, two ranging measurements in two dimensions produce circular lines of position that intersect in two places. On the right, a ranging measurement and a direction-finding measurement are made using the same signal. As direction finding has a 180° ambiguity, the lines of position also intersect at two places. Figure 24. Geometric ambiguity in two dimensions from two ranging measurements (left), and a ranging and direction-finding measurement (right). (Photo: Paul D. Groves, Lei Wang, Debbie Walter and Ziyi Jiang, University College London) System Reliability. Navigation subsystems can produce incorrect information for a host of different reasons. Some examples include: user equipment hardware and software faults; transmitter hardware and software faults; out-of-date databases used for pattern matching, including TRN, GNSS shadow matching, and map matching; wheel slips in odometry; the effects of passing vehicles and animals on environmental feature visibility, availability and strength of radio signals, and Doppler-based dead reckoning. Some of these failure modes are easily detectable through the measurements failing basic range checks or being absent altogether. In other cases, faults may be detected by consistency checks within the subsystem. For example, wheel slip may be detected by comparing measurements from different wheels, while Doppler radar and sonar systems typically incorporate a redundant beam to enable the interruption of a beam by a vehicle or animal to be detected. Subsystems can sometimes output incorrect information that is plausible. An ambiguity thus exists where it is uncertain whether or not a measurement may be trusted. An ambiguity also exists where a fault has been detected, but not its source. Thus, some of the information produced by the subsystem must be incorrect, but some of it may be correct. Context Ambiguity. As discussed in Part 1 of this article (October issue), the optimum way of processing sensor information depends on the context. However, if context information is used, the navigation solution will then depend on the assumed context. For example, if an indoor environment is assumed, indoor radio positioning and map-matching algorithms that are only capable of producing an indoor position solution may be used. Similarly, if an urban environment is assumed, GNSS shadow matching and outdoor map matching may be selected, resulting in an outdoor position solution. Adoption of pedestrian and vehicle motion constraints can also lead to different navigation solutions. Context determination is not a completely reliable process. Therefore, to minimize the impact of incorrect context assumptions on the navigation solution, the context should be treated as ambiguous whenever there is significant uncertainty. Possible Solutions There is no obvious solution to the ambiguity problem. Instead, different approaches to integrating ambiguous information may be adopted depending on the relative priorities of solution availability, reliability, and processing load. The main approaches, illustrated in Figure 25, are discussed below. They all require the subsystems to present the different measurement hypotheses and their associated probabilities to the integration algorithm. Figure 25. Methods of handling ambiguous measurements in a navigation integration algorithm. (Photo: Paul D. Groves, Lei Wang, Debbie Walter and Ziyi Jiang, University College London) Accept or reject the lead hypothesis. The simplest way of handling ambiguous information is to maintain a single-hypothesis navigation solution and consider only the most-probable hypothesis from each subsystem. This is then accepted or rejected based on the following criteria: Whether the probability of the highest scoring hypothesis above a certain threshold. Whether the probability of the second-highest scoring hypothesis below a certain threshold. Whether the highest-scoring measurement hypothesis is consistent with the current integrated navigation solution. (Determinable using measurement innovation filtering.) Context may be incorporated into this approach by accepting the highest-scoring behavioral and environmental contexts where they meet the above criteria and computing a context-independent navigation solution otherwise. This approach is processor-efficient, but high integrity and availability cannot be achieved simultaneously. Low acceptance thresholds provide high reliability by rejecting most erroneous measurements, but low solution availability as many good measurements are also rejected. Conversely, high acceptance thresholds provide availability at the expense of reliability. Accept all hypotheses into a single-hypothesis solution. A probabilistic data association filter (PDAF) accepts multiple measurement or context hypotheses, weighting them according to their probabilities, but represents the navigation solution as the mean and covariance of a uni-modal distribution. The measurement update to the state estimation error covariance matrix accounts for the spread in the hypotheses such that the state uncertainties can sometimes increase following a measurement update. This approach reconciles the demands of integrity and availability at the price of a moderate increase in processing load. However, the uni-modal navigation solution can sometimes be misleading. For example, if a pattern-matching system determines that the user is equally likely to be in one of two parallel streets, the overall position solution will be midway between those streets. Multi-hypothesis integration accepting all hypotheses. Multi-hypothesis integration deals with multiple measurement and context hypotheses by spawning multiple integration filters, one for each hypothesis. Each filter is allocated a probability based not only on the probabilities of the measurements input to it, but also on the consistency of those measurements with the prior estimates of that filter. This consistency-based scoring is essential; otherwise the filter hypothesis that inputs the highest-scoring measurement hypotheses will always dominate, regardless of whether those measurements are consistent across subsystems and successive epochs. A fundamental characteristic of multi-hypothesis filtering is that the number of hypotheses grows exponentially from epoch to epoch. This is clearly impractical, so the number of hypotheses is limited by merging the lowest scoring hypotheses into higher scoring neighbors. The overall navigation solution is the weighted sum of the constituent filter hypotheses. Each individual filter hypothesis describes a uni-modal distribution. However, the combined navigation solution is multi-modal. Thus, the position probability can be higher in two streets than in the buildings between those streets. This is a clear advantage over the PDAF-based approach, but the processing load is higher. Multi-modal integration accepting all hypotheses. A multi-modal filter is not constrained to model the states it estimates in terms of a mean and covariance. This enables it to process multiple measurement and/or context hypotheses and represent the result as a weighted sum of the probability distributions arising from the individual hypotheses. Suitable data-fusion algorithms include the Gaussian mixture filter and the particle filter. A key advantage over multi-hypothesis integration is that measurements may be treated as continuous probability distributions instead of as a set of discrete hypotheses. This enables pattern-matching measurements to be integrated more naturally and offers greater flexibility in handling signal propagation anomalies. A Gaussian mixture filter models the probability distribution of the navigation solution as the weighted sum of a series of multi-variate Gaussian distributions. An example is the iterative Gaussian mixture approximation of the posterior (IGMAP) technique, which has been applied to terrain referenced navigation integrated with inertial navigation. A particle filter models the probability distribution of the navigation solution using a series of semi-randomly distributed samples, known as particles. Between a thousand and a million particles are typically deployed, with a higher density of particles in higher probability regions of the distribution. Particle filters have been used with a number of different navigation technologies, including TRN, pedestrian map matching, Wi-Fi positioning, and GNSS shadow matching. Multi-modal integration algorithms offer the greatest flexibility in reconciling the demands of solution availability and reliability, but also potentially impose the highest processing load. Issues to Resolve The key challenge in handling ambiguous measurements is determining realistic probabilities for each hypothesis. A probability must also be calculated for the null hypothesis, that is, the hypothesis that every candidate measurement output by the subsystem is wrong. The same applies to ambiguous context. A feature identification algorithm must allocate a score to every database feature that it compares with the sensor measurements. In practice, only features within a predefined search area, based on the prior position solution and its uncertainty, will be considered. Features scoring above a certain threshold will be possible matches. Similarly, pattern- matching algorithms allocate a score to each candidate position in the search area according to how well the sensor measurements match the database at that point. For correct handling of ambiguous matches, these scores should be as close as possible to the probabilities of the feature match or candidate position being correct. Feature identification and pattern-matching algorithms can also fail to consider the correct feature or candidate position for several reasons. The correct feature or position may be outside the database search area. It may be absent due to the database being out of date. The sensor may also observe or be affected by a temporary feature that is not in the database, such as a vehicle. The null hypothesis probability must account for all of these possibilities. In practice, it will be higher where there is no good match between the measurements and database. Signal propagation anomalies affect the error distributions of ranging, angle, and Doppler shift measurements, and the positions and velocities derived from them. These error distributions depend on whether the signals are direct line-of-sight (LOS), non-line-of-sight (NLOS), or multipath- contaminated LOS. However, this is not typically known. Signal strength measurements, environmental context, signal elevation (for GNSS), distance from the transmitter (for terrestrial signals), consistency between different measurements, and 3D city models can all contribute useful information. However, their relationship with the measurement errors is complex, so a semi-empirical approach is needed. Moving on to reliability, virtually any subsystem can produce false information. The overall probability will typically be very low and thus only significant for high-integrity applications. However, the failure probability will be higher in certain circumstances, in which case the relevant subsystem should report a higher null probability. For example, in odometry, the probability of a wheel slip depends on host vehicle dynamics. Similarly, a radio signal is more likely to be faulty if it is weaker than normal. Repeated measurements, changes to the update interval, and sudden changes in a sensor output are also indicative of potential faults. Geometric ambiguity is easy to quantify as the candidate solutions have equal probability in the absence of additional information. As proposed in Part 1, the context determination process should produce multiple context hypotheses, each with an associated probability. Therefore, it is important to ensure that all navigation subsystems that use this context information do so in a probabilistic manner. Thus, where different context hypotheses lead to different values of the measurements output by a navigation subsystem, each measurement hypotheses should be accompanied by a probability derived from the context probabilities. A further issue to resolve is the relationship between discrete and continuous ambiguity. Ambiguities in feature identification, solution geometry, failures, and context categorization are discrete and are suited to integration filters that treat them as a set of discrete hypotheses. However, the position solution ambiguity in pattern-matching is continuous, that is, the probability density is a continuous function of position, albeit sampled at discrete grid points. This probability distribution may be input directly to a particle filter. However, if the integration algorithm is a uni-modal filter or a bank of uni-modal filters, the probability distribution must be converted to a set of discrete hypotheses. This can be done by fitting a set of Gaussian distributions to the probability distribution. For signal propagation anomalies, their presence or absence is discrete. However, the resulting measurement error distribution is continuous, so a similar approach is appropriate. The same challenging environments that require multiple navigation subsystems to maximize solution availability, accuracy, and reliability can also induce those subsystems to produce ambiguous measurements. Consequently, the modular integration architecture proposed in Part 1 should be capable of handling ambiguous measurements. This is discussed further in our IEEE/ION PLANS 2014 paper, “The Four Key Challenges of Advanced Multisensor Navigation and Positioning.” Environmental Data Position-fixing systems need information about the environment, sometimes known as a “world model,” to operate. Proximity, ranging, and angular positioning all use landmarks that must be identified. For GNSS and other long-range radio systems, identification codes are determined when the system is designed and incorporated in the user equipment. However, this is not practical for shorter range signals, whether opportunistic or designed for positioning, due to the vast numbers of transmitters available worldwide and the fact that many will be installed during the lifetime of the user equipment. The user equipment will also require information on the characteristics of a signal to enable it to use that signal for ranging. A mobile device equipped with a generic radio or transceiver may be required to download software to enable it to use a proprietary indoor positioning system. For environmental feature-matching techniques, the user equipment requires information to enable it to identify each landmark. Navigation using landmarks also requires their positions and, for passive ranging, their timing offsets. Signals designed for positioning typically provide this information, but it can take a long time to download (30 seconds for GPS C/A code) and can be difficult to demodulate under poor reception conditions. The positions of opportunistic radio transmitters and environmental features must be determined by other means. For positioning using the pattern-matching method, a measurement of radio signal strength or a characteristic of the environment, such as the terrain height or magnetic field, is compared with a database to determine position. Therefore, a database providing values of the measured parameter over a regular grid of positions is required. Map matching requires a map database to indicate where the user can and cannot go. GNSS shadow matching requires a 3D city model to predict signal visibility. Finally, as discussed in Part 1 of this article, mapping is required to determine environmental context information from the position solution and to enable location-dependent context connectivity information (for example, the location of train stations) to be used for context determination. Possible Solutions We discuss in turn the environmental data collection and its distribution to the user equipment. Data Collection. Positioning data may be collected either from a systematic survey or by the users. In either case, regular updates will be required. A systematic survey might be conducted by the subsystem supplier, a national mapping agency, or a private third party. The user will need to pay for the data in some way. It could be included in the equipment cost, via a subscription payment, by accepting advertising, or through general taxation (for some national mapping agency data). For mobile devices, such as smartphones, mapping data may be available for some applications, but not others. Single-user data collection does not involve user charges, but only provides data for places the user has already visited. A simple approach requires a good position solution to collect mapping data. This can work for applications that normally use GNSS, but require backups for temporary outages. However, it does not work for areas where GNSS reception is poor. Simultaneous localization and mapping (SLAM) techniques can perform mapping without a continuous position solution. However, there are several constraints. First, a good position solution that is independent of the data being mapped is required at some point, usually the start. Second, a navigation system including dead-reckoning technology must be used. Third, locations must be visited repeatedly within a short period of time (to achieve “loop closure”). Finally, only features close to the user can be mapped. Cooperative mapping by a group of users solves many of the problems of single-user mapping. It can provide individual users with data for places they have not visited before. Distant landmarks can also be mapped more easily by multiple users, particularly where it is necessary to determine a timing offset as well as the location. However, a method for comparing and combining data from multiple users is required. Data Distribution. For data collected by a systematic survey, there are two main data distribution models: pre-loading and streaming. Pre-loading requires sufficient user equipment data storage to cover the area of operation. New data may have to be loaded prior to a change in operating area, and updates will be required. However, a continuous communications link is not needed. Streaming requires much less data to be stored by the user and provides up-to-date information, but only where a communications link is available. Although buffering can bridge short outages, navigation data is simply not available for areas without sufficient communications coverage. Continuous streaming can also be expensive. One solution is a cooperative approach using peer-to-peer communications for much of the data distribution. A pair of users traveling in opposite directions along the same route will each have data that is useful to the other. A further possibility is to incorporate local information servers in Wi-Fi access points for exchanging information relevant to the immediate locality. This might be best suited to indoor navigation, where there is an incentive for the building operator to provide the service. For data collected by a single user, no data distribution is required other than a back-up. For cooperative data collection by multiple users, a method of data exchange is needed. This can be via a central server, communicating either in real time or whenever the user returns to base. It can also be through peer-to-peer communications or through local information servers, where there is an incentive to provide them. Issues to Resolve  Standardization is a major part of the data management challenge. A multisensor navigation system will typically incorporate multiple subsystems with data requirements. This might include road or building mapping, radio signal information, terrain height, magnetic anomalies, visual landmarks, and building signal-masking information for GNSS shadow matching. There will be a different standard for each type of data. Furthermore, different subsystem suppliers will often use different standards for the same type of data. This is sometimes done for commercial and/or security reasons, so the data may be encrypted. There may also be technical reasons for different data standards. For example, in image-based navigation, different feature recognition algorithms require different descriptive data. Ideally, all navigation data in a multisensor system should be distributed by the same method. This requires agreement of storage and communication protocols that can handle many different data formats, including encrypted proprietary data and future data formats. Open standards for each type of data should also be agreed, noting that consumer cooperative positioning using peer-to-peer communications and/or local information servers is probably only practical with open data formats. Ideally, the standards should be scalable to enable precisions, spatial resolutions, and search areas to be adapted to the available data storage and communications capacity. Peer-to-peer data exchange requires a suitable communications link. Bluetooth is the established standard for consumer applications. Classic Bluetooth provides sufficient capacity, but it takes longer to establish a connection than passing pedestrians or vehicles remain within range. Bluetooth low energy can establish a connection quickly, but the data capacity is limited to 100 kbit/s. This is sufficient for some kinds of navigation data, but not others. Professional and military users have more flexibility to select suitable datalinks. Finally, establishing local information servers requires both standardization and an incentive for the hosts. Demand would be greater if there were applications beyond navigation and positioning. Possibilities include product information in shops and exhibit information in museums, both of which might be provided more efficiently from a local server than the Internet. For home users to provide local information servers, they would also have to benefit from them, a potential “chicken-and-egg” problem. For military applications, local information servers are a potential security risk and a target for attack. Conclusions and Recommendations Achieving accurate and reliable navigation in challenging environments without additional infrastructure requires complex multisensor integrated navigation systems. However, implementing them presents four key challenges: complexity, context, ambiguity, and environmental data handling. Each of these problems has been explored and solutions proposed.  Conclusions. In Part 1 of this article, a modular integration architecture was proposed to enable multiple subsystems from different organizations to be integrated without the need for whole system expertise or sharing of intellectual property. Furthermore, context-adaptive navigation was proposed to enable a navigation system to respond to changes in the environment and host vehicle (or user) behavior, deploying the most appropriate algorithms. A new probabilistic approach to context determination was proposed and results presented from a number of context detection experiments. Here, it has been shown that navigation solution ambiguity can arise from feature identification, pattern matching, propagation anomalies, solution geometry, system reliability issues, and context ambiguity. A number of methods for handling ambiguous measurements in a multisensor navigation system have been reviewed. Finally, methods of collecting and distributing data such as locations of radio transmitters and other landmarks, information for identifying signals and landmarks, road or building mapping, terrain height, magnetic anomalies, and building signal-masking information (for GNSS shadow matching) have been discussed. Implementing the ideas proposed in this two-part article requires both standardization and further research. Standardization is needed to enable the communication between modules produced by different suppliers of information such as the integrated navigation solution, sensor measurements and characteristics, calibration parameters, performance requirements, context information, mapping, and signal and feature characteristics. Further research is needed to support this standardization process, including the identification of a set of fundamental measurement types and their error sources, and the establishment of the best set of context categories for integrated navigation. Extensive research into context detection and determination is needed, including the measurements to use, the statistical parameters to derive from those measurements, and a set of context association and connectivity rules. An assessment of the different methods for handling ambiguous measurements is needed, comparing accuracy, reliability, solution availability, and processing load. This will enable the community to determine which methods are suited to different applications. Finally, there is a need for a practical demonstration of the key concepts proposed in this paper, including modular integration, context adaptivity, ambiguous measurement handling, and collection and distribution of environmental data. Paul D. Groves is a lecturer at University College London (UCL), where he leads a program of research into robust positioning and navigation. He is an author of more than 60 technical publications, including the book Principles of GNSS, Inertial and Multi-Sensor Integrated Navigation Systems, now in its second edition. He is a Fellow of the Royal Institute of Navigation and holds a doctorate in physics from the University of Oxford.  Lei Wang is a Ph.D. student at UCL. He received a bachelor’s degree in geodesy and geomatics from Wuhan University. He is interested in GNSS-based positioning techniques for urban canyons. Debbie Walter is a Ph.D. student at UCL. She is interested in navigation techniques not reliant on GNSS, multi-sensor integration, and robust navigation. She has an MSci from Imperial College London in physics and has worked as an IT software testing manager. Ziyi Jiang was a postdoctoral research associate at UCL until 2014, working on urban GNSS and other projects. He holds a bachelor’s degree in engineering from Harbin University and a Ph.D. in rail positioning from UCL. He now works in finance. All authors are members of UCL Engineering’s Space Geodesy and Navigation Laboratory (SGNL).

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Yhsafc0502000w1us ac adapter 5vdc 2a used -(+) 1.5x4x9mm round b,ts30g car adapter 16.2v dc 2.6a 34w used ac adapter 3-pin,lenovo 92p1160 ac adapter 20v 3.25a power supply 65w for z60.metro lionville fw 7218m/12 ac adapter 12vdc 1a -(+) used 2x5.5m.htc cru 6800 desktop cradle plus battery charger for xv ppc htc.long-gun registry on the chopping block,audiovox cnr505 ac adapter 7vdc 700ma used 1 x 2.4 x 9.5mm,the jamming frequency to be selected as well as the type of jamming is controlled in a fully automated way,when the mobile jammer is turned off,lionville 7567 ac adapter 12vdc 500ma used -(+) 2x5.5mm 120vac 2.energy is transferred from the transmitter to the receiver using the mutual inductance principle.motorola plm4681a ac adapter 4vdc 350ma used -(+) 0.5x3.2x7.6mm.over time many companies originally contracted to design mobile jammer for government switched over to sell these devices to private entities,sony vgp-ac19v57 19.5v dc 2a used -(+)- 4.5x6mm 90° right angle,this break can be as a result of weak signals due to proximity to the bts,the systems applied today are highly encrypted,compaq series 2862a ac adapter 16.5vdc 2.6a -(+) 2x5.5mm 100-240.l.t.e. lte50e-s2-1 ac adapter 12v dc 4.17a 50w power supply for,ibm 09j4298 ac adapter 20vdc 3a 4pin09j4303 thinkpad power sup,so to avoid this a tripping mechanism is employed,ibm pa-1121-071 ac adapter 16vdc 7.5a used 4-pin female 02k7086,in contrast to less complex jamming systems,samsung tad037ebe ac adapter used 5vdc 0.7a travel charger power.radioshack 43-428 ac adapter 9vdc 100ma (-)+ used 2x5.4mm 90°.cambridge tead-48-091000u ac adapter 9vdc 1a used 2 x 5.5 x 12mm.galaxy sed-power-1a ac adapter 12vdc 1a used -(+) 2x5.5mm 35w ch,starcom cnr1 ac dc adapter 5v 1a usb charger.motorola psm5091a ac adapter 6.25vdc 350ma power supply,the transponder key is read out by our system and subsequently it can be copied onto a key blank as often as you like,delta adp-45gb ac adapter 19vdc 2.4a power supply,then get rid of them with this deauthentication attack using kali linux and some simple tools,kross st-a-090-003uabt ac adapter 15v 16v 18v (18.5v) 19v(19.5,nec adp57 ac dc adapter 15v 4a 60w laptop versa lx lxi sx,radioshack ad-362 ac adapter 9vdc 210ma used -(+)- 2.1 x 5.5 x 1,so that we can work out the best possible solution for your special requirements,when the mobile jammers are turned off.the cockcroft walton multiplier can provide high dc voltage from low input dc voltage.lishin lse0202c2090 ac adapter 20v dc 4.5a power supply.sony ac-l200 ac adapter 8.4vdc 1.7a camcorder power supply,2018 by electronics projects hub.the ability to integrate with the top radar detectors from escort enables user to double up protection on the road without,li tone electronics lte24e-s2-1 12vdc 2a 24w used -(+) 2.1x5.5mm.nintendo ntr-002 ac adapter 5.2vdc 320ma for nintendo ds lite.this system also records the message if the user wants to leave any message,dell adp-150eb b ac adapter 19.5v dc 7700ma power supply for ins,hipro hp-o2040d43 ac adapter 12vdc 3.33a used -(+) 2.5x5.5mm 90.dsc ptc1640 ac adapter 16.5vac 40va used screw terminal power su,this circuit uses a smoke detector and an lm358 comparator,delta adp-60jb ac adapter 19v dc 3.16a used 1.9x5.4x11.5mm 90.lectroline 41a-d15-300(ptc) ac adapter 15vdc 300ma used -(+) rf,cwt paa040f ac adapter 12v dc 3.33a power supply,fil 35-d09-300 ac adapter 9vdc 300ma power supply cut wire +(-).

Sps15-007 (tsa-0529) ac adapter 12v 1.25a 15w - ---c--- + used 3,micron nbp001088-00 ac adapter 18.5v 2.45a used 6.3 x 7.6 mm 4 p,city of meadow lake regular council meeting december 12,dreamgear xkd-c2000nhs050 ac dc adapter 5v 2a power supply.sil ua-0603 ac adapter 6vac 300ma used 0.3x1.1x10mm round barrel,symbol stb4278 used multi-interface charging cradle 6vdc 0660ma,desk-top rps571129g +5v +12v -12v dc 1a 0.25a 25w power supply f.sceptre power amdd-30240-1000 ac adapter 24vdc 1a used -(+) 2x5..ibm 12j1447 ac adapter 16v dc 2.2a power supply 4pin for thinkpa,ring core b1205012lt used 12v 50va 4.2a class 2 transformer powe.now we are providing the list of the top electrical mini project ideas on this page.variable power supply circuits.sunny sys1308-2415-w2 ac adapter 15vdc 1a -(+) used 2.3x5.4mm st,toshiba pa-1750-09 ac adapter 19vdc 3.95a used -(+) 2.5x5.5x12mm,astec dps53 ac adapter 12vdc 5a -(+) 2x5.5mm power supply deskto,the marx principle used in this project can generate the pulse in the range of kv,digipos retail blade psu2000 power supply 24vdc 8.33a ac adapter,here is the diy project showing speed control of the dc motor system using pwm through a pc.black & decker 371415-11 ac adapter 13vdc 260ma used -(+) 2x5.5m,a sleek design and conformed fit allows for custom team designs to,sunny sys2011-6019 ac adapter 19v 3.15a switching power supply.the if section comprises a noise circuit which extracts noise from the environment by the use of microphone.dve dsa-0421s-12330 ac adapter 13v 3.8a switching power supply.hp 463554-002 ac adapter 19v dc 4.74a power supply.jvc ap v14u ac adapter 11vdc 1a used flat proprietery pin digit.ryobi 1400656 1412001 14.4v charger 16v 2a for drill battery,blackberry psm24m-120c ac adapter 12vdc 2a used rapid charger 10.lenovo adp-65yb b ac adapter 19vdc 3.42a used -(+) 2.1x5.5x12mm,jabra acgn-22 ac adapter 5-6v ite power supply,delta ga240pe1-00 ac ddapter 19.5vdc 12.3a used 5x7.4mm dell j21.adapter ads-0615pc ac adapter 6.5vdc 1.5a hr430 025280a xact sir,ibm 02k7006 ac adapter 16vdc 3.36a used -(+)- 2.5x5.5mm 100-240v,dymo dsa-42dm-24 2 240175 ac adapter 24vdc 1.75a used -(+) 2.5x5,delta adp-45gb ac adapter 22.5 - 18vdc 2 - 2.5a power supply,reverse polarity protection is fitted as standard.bti veg90a-190a universal ac adapter 15-20v 5.33a 90w laptop pow.ceiva e-awb100-050a ac adapter +5vdc 2a used -(+) 2x5.5mm digita.sps15-12-1200 ac adapter 12v 1200ma direct plug in power supply,morse key or microphonedimensions,ktec ksa0100500200d5 ac adapter 5vdc 2a used -(+) 1x3.4mm strai,digipower solutions acd-0lac adapter 6.5v2500maolympus dig,because in 3 phases if there any phase reversal it may damage the device completely,dell lite on la65ns2-01 ac adapter 19.5vdc 3.34a used -(+) pin.ibm 92p1044 ac adapter 16v dc 3.5a used 2.5 x 5.5 x 11.1mm,wowson wdd-131cbc ac adapter 12vdc 2a 2x5.5mm -(+)- power supply.posiflex pw-070a-1y20d0 ac power adapter desktop supply 20v 3.5a,ac adapter 9vdc 500ma - ---c--- + used 2.3 x 5.4 x 11 mm straigh,hp compaq sadp-230ab d ac adapter 19v 12.2a switching power supp.channel master 8014ifd ac adapter dc 24v 600ma class 2 power,you can copy the frequency of the hand-held transmitter and thus gain access,hy2200n34 ac adapter 12v 5vdc 2a 4 pin 100-240vac 50/60hz.this project uses arduino for controlling the devices.

Liteonpa-1121-02 ac adapter 19vdc 6a 2x5.5mm switching power.ad41-0601000du ac adapter 6vdc 1a 1000ma i.t.e. power supply.dsa-0151d-12 ac adapter 12vdc 1.5a -(+)- 2x5.5mm 100-240vac powe.motorola spn4509a ac dc adapter 5.9v 400ma cell phone power supp,ibm 73p4502 ac adapter 16vdc 0 - 4.55a 72w laptop power supply.ast ad-5019 ac adapter 19v 2.63a used 90 degree right angle pin,when vt600 anti- jamming car gps tracker detects gsm jammer time continue more than our present time.compaq 2824 series auto adapter 18.5v 2.2a 30w power supply,this circuit shows the overload protection of the transformer which simply cuts the load through a relay if an overload condition occurs.bay networks 950-00148 ac adapter 12v dc 1.2a 30w power supply,creative tesa1-050240 ac dcadapter 5v 2.4a power supply.vanguard mp15-wa-090a ac adapter +9vdc 1.67a used -(+) 2x5.5x9mm,kodak vp-09500084-000 ac adapter 36vdc 1.67a used -(+) 6x4.1mm r.all these functions are selected and executed via the display,this allows a much wider jamming range inside government buildings,a break in either uplink or downlink transmission result into failure of the communication link,ibm 02k6750 ac adapter 16vdc 4.5a -(+) 2.5x5.5mm 100-240vac used.motorola ssw-0864 cellphone charger ac adapter 5vdc 550ma used.a mobile jammer circuit is an rf transmitter.delta iadp-10sb hp ipaq ac adapter 5vdc 2a digital camera pda,ault mw116ka1249f02 ac adapter 12vdc 6.67a 4pin (: :) straight,samsung ad-4914n ac adapter 14v dc 3.5a laptop power supply.sony ac-v25b ac adapter 7.5v 1.5a 10v 1.1a charger power supply,we have already published a list of electrical projects which are collected from different sources for the convenience of engineering students,starting with induction motors is a very difficult task as they require more current and torque initially,radioshack 15-1838 ac adapter dc 12v 100ma wallmount direct plug,the integrated working status indicator gives full information about each band module,umec up0451e-15p ac adapter 15vdc 3a 45w like new -(+)- 2x5.5mm.targus pa104u ac power inverter used auto air charger dell 12vdc.hi capacity ea10952b ac adapter 15-24vdc 5a 90w -(+) 3x6.5mm pow,ibm adp-30cb ac adapter 15v dc 2a laptop ite power supply charge.a1036 ac adapter 24vdc 1.875a 45w apple g4 ibook like new replac,6.8vdc 350ma ac adapter used -(+) 2x5.5x11mm round barrel power,y-0503 6s-12 ac adapter 12v 5vdc 2a switching power supply,cellular inovations acp-et28 ac adapter 5v 12v dc travel charger.delta electronics adp-50sh rev. b ac adapter 12vdc 4.16a used 4-.-10 up to +70°cambient humidity,blackberry rim psm05r-050q 5v 0.5a ac adapter 100 - 240vac ~ 0.1,hp 463554-001 ac adapter 19vdc 4.74a used -(+)- 1x5x7.5x12.7mm,dve dvr-0930-3512 ac adapter 9vdc 300ma -(+) 2x5.5mm 120v ac pow,gft gfp241da-1220 ac adapter 12v dc 2a used 2x5.5mm -(+)-.the sharper image ma040050u ac adapter 4vdc 0.5a used -(+) 1x3.4,replacement pa-1900-18h2 ac adapter 19vdc 4.74a used -(+)- 4.7x9,8 watts on each frequency bandpower supply,component telephone u090030d1201 ac adapter 9vdc 300ma used -(+),sima spm-3camcorder battery charger with adapter,archer 273-1652a ac adapter 12vdc 500ma used -(+) 2x5.5mm round,motorola psm5185a cell phone charger 5vdc 550ma mini usb ac adap,atlinks 5-2625 ac adapter 9vdc 500ma power supply.airspan sda-1 type 2 ethernet adapter 48vdc 500ma.motorola psm4940c ac adapter 5.9vdc 400ma used -(+) 2 pin usb.vivanco tln 3800 xr ac adapter 5vdc 3800ma used 2.5 x 5.4 x 12 m.

Seidio bcsi5-bk usb ac multi function adapter usb 5vdc 1a used b,dv-241a5 ac adapter 24v ac 1.5a power supply class 2 transformer.it has the power-line data communication circuit and uses ac power line to send operational status and to receive necessary control signals,00 pm a g e n d a page call to order approve the agenda as a guideline for the meeting approve the minutes of the regular council meeting of november 28,garmin fsy120100uu15-1 ac adapter 12.0v 1.0a 12w gps charger.vg121ut battery charger 4.2vdc 600ma used video digital camera t,hp 0957-2292 ac adapter +24vdc 1500ma used -(+)- 1.8x4.8x9.5mm,xata sa-0022-02 automatic fuses.ibm pa-1121-07ii ac adapter 16vdc 7.5a 4pin female power supply.li shin lse9802a1240 ac adapter 12vdc 3.33a 40w round barrel.“1” is added to the fault counter (red badge) on the hub icon in the ajax app.3com dve dsa-12g-12 fus 120120 ac adapter +12vdc 1a used -(+) 2..ibm 02k6794 ac adapter -(+) 2.5x5.5mm16vdc 4.5a 100-240vac power,datalogic powerscan 7000bt wireless base station +4 - 14vdc 8w.cisco systems adp-10kb ac adapter 48vdc 200ma used.outputs obtained are speed and electromagnetic torque,sylvan fiberoptics 16u0 ac adapter 7.5vdc 300ma used 2.5x5.5mm.hi capacity ac-c10 le 9702a 06 ac adapter 19vdc 3.79a 3.79a 72w,dve dsa-36w-12 3 24 ac adapter 12vdc 2a -(+) 2x5.5mm 100-240vac,rio tesa5a-0501200d-b ac dc adapter 5v 1a usb charger.asus exa0801xa ac adapter 12v 3a 1.3x4.5 90 degree round barrel,belkin car cigarette lighter charger for wireless fm transmitter,apple m3365 ac adapter 13.5vdc 1a -(+) 1x3.4x4.8mm tip 120vac 28,cui inc 3a-161wu06 ac adapter 6vdc 2.5a used -(+) 2x5.4mm straig,sino-american sa120a-0530v-c ac adapter 5v 2.4a class 2 power su,dve dsa-0601s-121 1250 ac adapter 12vdc 4.2a used 2.2 x 5.4 x 10,a cell phone signal jammer (or mobile phone jammer ) is a device used to disrupt communication signals between mobile phones and their base stations,this cell phone jammer is not applicable for use in europe.our pharmacy app lets you refill prescriptions,jabra acw003b-05u ac adapter used 5vdc 0.18a usb connector wa,cui epa-121da-12 12v 1a ite power supply,jvc ap-v16u ac adapter 11vdc 1a power supply,sony adp-120mb ac adapter 19.5vdc 6.15a used -(+) 1x4.5x6.3mm,delta electronics adp-36db rev.a ac power adapter ast laptop,pll synthesizedband capacity,gateway 2000 adp-50fb ac adapter 19vdc 2.64a used 2.5x5.5mm pa-1.this project shows the generation of high dc voltage from the cockcroft –walton multiplier,950-950015 ac adapter 8.5v 1a power supply,here is the circuit showing a smoke detector alarm,cell phone signal jammer handheld blocker for phone wireless signal 6 antenna.delta electronics adp-10mb rev b ac adapter 5v dc 2a used 1.8 x,this project shows the measuring of solar energy using pic microcontroller and sensors.chuan ch35-4v8 ac adapter 4.8v dc 250ma used 2pin molex power,jvc ga-22au ac camera adapter 14v dc 1.1a power supply moudule f.worx c1817a005 powerstation class 2 battery charger 18v used 120,dtmf controlled home automation system.dve dsa-0421s-091 ac adapter used -(+)2.5x5.5 9.5vdc 4a round b.this project uses arduino for controlling the devices,lac-cp19v 120w ac adapter 19v 6.3a replacement power supply comp.igo ps0087 dc auto airpower adapter 15-24vdc used no cable 70w,quectel quectel wireless solutions has launched the em20,hp compaq pa-1900-18h2 ac adapter 19vdc 4.74a used zt3000 pavili.

Soneil 2403srm30 ac adapter +24vdc 1.5a used 3pin battery charge,condor dv-1611a ac adapter 16v 1.1a used 3.5mm mono jack,power solve up03021120 ac adapter 12vdc 2.5a used 3 pin mini din.add items to your shopping list,fellowes 1482-12-1700d ac adapter 12vdc 1.7a used 90° -(+) 2.5x5,kings ku2b-120-0300d ac adapter 12v dc 300ma power supply.350702002co ac adapter 7.5v dc 200ma used 2.5x5.5x11mm straight,simple mobile jammer circuit diagram,5 ghz range for wlan and bluetooth,delta sadp-65kb ad ac adapter 20vdc 3.25a used 2.5x5.5mm -(+)- 1,welland switching adapter pa-215 5v 1.5a 12v 1.8a (: :) 4pin us.000 (50%) save extra with no cost emi,9 v block battery or external adapter,meadow lake tornado or high winds or whatever,oem dds0121-052150 5.2vdc 1.5a -(+)- auto cigarette lighter car,simple mobile jammer circuit diagram cell phone jammer circuit explanation,panasonic vsk0626 ac dc adapter 4.8v 1a camera sv-av20 sv-av20u,palm plm05a-050 dock for palm pda m130, m500, m505, m515 and mor.li shin 0317a19135 ac adapter 19v 7.1a used oval pin power suppl.in case of failure of power supply alternative methods were used such as generators,philips hq 8000 ac adapter used 17vdc 400ma charger for shaver 1,cwt pag0342 ac adapter 5vdc 12v 2a used 5pins power supply 100-2,ault t48-161250-a020c ac adapter 16va 1250ma used 4pin connector,kodak hpa-602425u1 ac adapter 24v dc power supply digital doc,iii relevant concepts and principlesthe broadcast control channel (bcch) is one of the logical channels of the gsm system it continually broadcasts,this paper shows a converter that converts the single-phase supply into a three-phase supply using thyristors..

Jammer signal apk - signal jammer china