Gps car tracker signal jammer gun - gps car tracker signal jammer device

A performance assessment demonstrates the ability of a networked group of users to locate themselves and each other, navigate, and operate under adverse conditions in which an individual user would be impaired. The technique for robust GPS positioning in a dynamic sensor network uses a distributed GPS aperture and RF ranging signals among the network nodes. By Dorota A. Grejner-Brzezinska, Charles Toth, Inder Jeet Gupta, Leilei Li, and Xiankun Wang In situations where GPS signals are subject to potential degradations, users may operate together, using partial satellite signal information combined from multiple users. Thus, collectively, a network of GPS users (hereafter referred to as network nodes) may be able to receive sufficient satellite signals, augmented by inter-nodal ranging measurements and other sensors, such as inertial measurement unit (IMU), in order to form a joint position solution. This methodology applies to numerous U.S. Department of Defense and civilian applications, including navigation of dismounted soldiers, emergency crews, on-the-fly formation of robots, or unmanned aerial vehicle (UAV) swarms collecting intelligence, disaster or environmental information, and so on, which heavily depend on availability of GPS signals. That availability may be degraded by a variety of factors such as loss of lock (for example, urban canyons and other confined and indoor environments), multipath, and interference/jamming. In such environments, using the traditional GPS receiver approach, individual or all users in the area may be denied the ability to navigate. A network of GPS receivers can in these instances represent a spatially diverse distributed aperture, which may be capable of obtaining gain and interference mitigation. Further mitigation is possible if selected users (nodes) use an antenna array rather than a single-element antenna. In addition to the problem of distributed GPS aperture, RF ranging among network nodes and node geometry/connectivity forms another topic relevant to collaborative navigation. The challenge here is to select nodes, which can receive GPS signals reliably, further enhanced by the distributed GPS aperture, to serve as pseudo-satellites for the purpose of positioning the remaining nodes in the network. Collaborative navigation follows from the multi-sensor navigation approach, developed over the past several years, where GPS augmentation was provided for each user individually by such sensors as IMUs, barometers, magnetometers, odometers, digital compasses, and so on, for applications ranging from pedestrian navigation to georegistration of remote sensing sensors in land-based and airborne platforms. Collaborative Navigation The key components of a collaborative network system are inter-nodal ranging sub-system (each user can be considered as a node of a dynamic network); optimization of dynamic network configuration; time synchronization; optimum distributed GPS aperture size for a given number of nodes; communication sub-system; and selection of master or anchor nodes. Figure 1 illustrates the concept of collaborative navigation in a dynamic network environment. Sub-networks of users navigating jointly can be created ad hoc, as indicated by the circles. Some nodes (users) may be parts of different sub-networks. FIGURE 1. Collaborative navigation concept. In a larger network, the selection of a sub-network of nodes is an important issue, as in case of a large number of users in the entire network, computational and communication loads may not allow for the entire network to be treated as one entity. Still, information exchange among the sub-networks must be assured. Conceptually, the sub-networks can consist of nodes of equal hierarchy or may contain master (anchor) nodes that normally have a better set of sensors and collect measurements from all client nodes to perform a collaborative navigation solution. Table 1 lists example sensors and techniques that can be used in collaborative navigation. TABLE 1. Typical sensors for multi-sensor integration: observables and their characteristics, where X,Y,Z are the 3D coordinates, vx, vy, vz are the 3D velocities, The concept of a master node is also crucial from the stand point of distributed GPS aperture, where it is mandatory to have master nodes responsible for combining the available GPS signals. Master nodes or some selected nodes will need anti-jamming protection to be effective in challenged electromagnetic (EM) environments. These nodes may have stand-alone anti-jamming protection systems, or can use the signals received by antennas at various nodes for nulling the interfering signals. Research Challenges Finding a solution that renders navigation for every GPS user within the network is challenging. For example, within the network, some GPS nodes may have no access to any of the satellite signals, and others may have access to one or more satellite signals. Also, the satellite signals received collectively within the network of users may or may not have enough information to determine uniquely the configuration of the network. A methodology to integrate sensory data for various nodes to find a joint navigation solution should take into account: acquisition of reliable range measurements between nodes (including longer inter-nodal distances); limitation of inter-nodal communication (RF signal strength); assuring time synchronization between sensors and nodes; and limiting computational burden for real time applications. Distributed GPS Apertures In the case of GPS signal degradation due to increased path loss and radio frequency interference (RFI), one can use an antenna array at the receiver site to increase the gain in the satellite signal direction as well as steer spatial nulls in the interfering signal directions. For a network of GPS users, one may be able to combine the signals received at various receivers (nodes) to achieve these goals (beam pointing and null steering); see Figure 2. Figure 2. Distributed antenna array. However, a network of GPS users represents a distributed antenna aperture with large (hundreds of wavelengths) inter-element spacing. This large thinned antenna aperture has some advantage and many drawbacks. The main advantage is increased spatial resolution which allows one to discriminate between signals sources with small angular separations. The main drawback is very high sidelobes (in fact, grating lobes) which manifest as grating nulls (sympathetic nulls) in null steering. The increased inter-element spacing will also lead to the loss of correlation between the signals received at various nodes. Thus, space-only processing will not be sufficient to increase SNR by combining the satellite signals received at various nodes. One has to account for the large delay between the signals received at various nodes. Similarly, for adaptive null steering, one has to use space-time adaptive processing (STAP) for proper operation. These research challenges must be solved for distributed GPS aperture to become a reality: Investigate the increase in SNR that can be obtained by employing distributed GPS apertures (accounting for inaccuracies in the inter-nodal ranging measurements). Investigate the improvement in the signal-to-interference-plus-noise ratio (SINR) that can be obtained over the upper hemisphere when a distributed GPS aperture is used for adaptive null steering to suppress RFI in GPS receivers. Obtain an upper bound for inter-node distances. Based on the results of the above two investigations, develop approaches for combined beam pointing and null steering using distributed GPS apertures. Inter-Nodal Ranging Techniques In a wireless sensor network, an RF signal can be used to measure ranges between the nodes in various modes. For example, WLAN observes the RF signal strength, and UWB measures the time of arrival, time difference of arrival, or the angle of arrival. There are known challenges, for example, signal fading, interference or multipath, to address for a RF-based technique to reliably serve as internodal ranging method. Ranging Based on Optical Sensing. Inter-nodal range measurements can be also acquired by active and passive imaging sensors, such as laser and optical imaging sensors. Laser range finders that operate in the eye-safe spectrum range can provide direct range measurements, but the identification of the object is difficult. Thus, laser scanners are preferred, delivering 3D data at the sensor level. Using passive imagery, such as digital cameras, provides a 2D observation of the object space; more information is needed to recover 3D information; the most typical techniques is the use of stereo pairs or, more generally, multiple-image coverage. The laser has advantages over optical imagery as it preserves the 3D object shapes, though laser data is more subject to artifacts due to non-instantaneous image formation. In general, regardless whether 2D or 3D imagery is used, the challenge is to recognize the landmark under various conditions, such as occlusions and rotation of the objects, when the appearance of the landmark alternates and the reference point on the landmark needs to be accurately identified, to compute the range to the reference point with sufficient accuracy. Network Configuration Nodes in the ad hoc network must be localized and ordered considering conditions, such as type of sensors on the node (grade of the IMU), anti-jamming capability, positional accuracy, accuracy of inter-nodal ranging technique, geometric configuration, computational cost requirements, and so on. There are two primary types of network configurations used in collaborative navigation: centralized and distributed. Centralized configuration is based on the concept of server/master and client nodes. Distributed configuration refers to the case where nodes in the network can be configured without a master node, that is, each node can be considered equal with respect to other nodes. Sensor Integration The selection of data integration method is an important task; it should focus on arriving at an optimal solution not only in terms of the accuracy but also taking the computational burden into account. The two primary options are centralized and decentralized extended Kalman filter (EKF). Centralized filter (CF) represents globally optimal estimation accuracy for the implemented system models. Decentralized filter (DF) is based on a collection of local filters whose solutions can be combined by a single master filter. DFs can be further categorized based on information-sharing principles and implementation modes. Centralized, Decentralized EKF. These two methods can provide comparable results, with similar computational costs for networks up to 30 nodes. Figures 3–5 describe example architectures of centralized/decentralized EKF algorithms. In Figure 3, all measurements collected at the nodes and the inter-nodal range measurements are processed by a single centralized EKF. Figures 4 and 5 illustrate the decentralized EKF with the primary difference between them being in the methods of applying the inter-nodal range measurements. The range measurements are integrated with the observations of each node by separate EKF per node in Figure 4, while Figure 5 applies the master filter to integrate the range measurements with the EKF results of all participating nodes. FIGURE 3. Centralized extended Kalman filter. FIGURE 4. Decentralized EKF, option 1. FIGURE 5. Decentralized EKF, option 2. Performance Evaluation To provide a preliminary performance evaluation of an example network operating in collaborative mode, simulated data sets and actual field data were used. Figure 6 illustrates the field test configuration, showing three types of nodes, whose trajectories were generated and analyzed. FIGURE 6. Collaborative navigation field test configuration. Nodes A1, A2, and A3 were equipped with GPS and tactical grade IMU, node B1 was equipped with GPS and a consumer grade IMU, and node C1 was equipped with a consumer grade IMU only. The following assumptions were used: all nodes were able to communicate; all sensor nodes were time-synchronized; nodal range measurements were simulated from GPS coordinates of all nodes; and the accuracy of GPS position solution was 1–2 meters/coordinate (1s); the accuracy of inter-nodal range measurements was 0.1meters (1s); all measurements were available at 1 Hz rate; the distances between nodes varied from 7 to 70 meters. Individual Navigation Solution. To generate the navigation solution for specific nodes, either IMU or GPS measurements or both were used. Since the reference trajectory was known, the absolute value of the differences between the navigation solution (trajectory) and the reference trajectory (ground truth) were considered as the navigation solution error. Figure 7 illustrates the absolute position error for the sample of 60 seconds of simulated data, with a 30-second GPS outage for nodes A1, A2, A3 and B1 (node C1 is not shown, as its error in the end of the test period was substantially bigger than that of the remaining nodes. Table 2 shows the statistics of the errors of each individual node’s trajectory for different sensor configurations. FIGURE 7. GPS/IMU positioning error for A1, A2, A3, B1 (includes a 30-second GPS outage.) Collaborative Solution. In this example, collaborative navigation is implemented after acquiring the individual navigation solution of each node, which was estimated with the local sensor measurements. The collaborative navigation solution is formed by integrating the inter-nodal range measurements to other nodes in a decentralized Kalman filter, which is referred to as “loose coupling of inter-nodal range measurements.” The test results of different scenarios are listed in Table 3. For cases labeled “30-sec GPS outage,” the GPS outage is assumed at all nodes that are equipped with GPS. The results listed in Table 3 indicate a clear advantage of collaborative navigation for nodes with tactical and consumer grade IMUs, particularly during GPS outages. When GPS is available (see, for example, node A1) the individual and collaborative solutions are of comparable accuracy. The next experiment used tight coupling of inter-nodal range measurements at each node’s EKF in order to calibrate observable  IMU errors even during GPS outages. In addition, varying numbers of master nodes are considered in this example. The tested data set was 600 seconds long, with repeated simulated 60-second GPS gaps, separated by 10-second periods of signal availability. The inter-nodal ranges were ~20 meters. Table 4 and Figure 8 summarize the navigation solution errors for collaborative solution of node C1 equipped with consumer grade IMU only, supported by varying quality other nodes. The error of the individual solution for this node in the end of the 600-second period reach nearly 250 kilometers (2D). Even for the case with a single anchor node (A1), the accuracy of the 2D solution is always better than 2 meters. Another 900-second experimental data with repeated GPS 60-second gaps on B1 node was analyzed with inter-nodal ranging up to 150 meters. Table 5 summarizes the results for C1 node. FIGURE 8. Absolute error for IMU-only and collaborative navigation solutions of C1 (GPS outage.) Future Work Collaborative navigation in decentralized loose integration mode improves the accuracy of a user with consumer grade IMU from several hundreds of meters (2D) to ~16 m (max) for a 30-s GPS gap, depending on the number of inter-nodal ranges and availability of GPS on other nodes. For a platform with GPS and consumer grade IMU (node B1) the improvement is from a few tens of meters to below 10 m. Better results were obtained when tight integration mode was applied, that is, inter-nodal range measurements were included directly in each EKF that handles measurement data collected by each individual node (architecture shown in Figure 4). For repeated 60-second GPS gaps, separated by 10-second signal availability, collaborative navigation maintains the accuracy at ~1–2 meter level for entire 600 s tested for nodes C1 and B1. Even though the preliminary simulation results are promising, more extended dynamic models and operational scenarios should be tested. Moreover, it is necessary to test the decentralized scenarios 1 and 2 (Figures 4–5) and then compare them with the centralized integration model shown in Figure 3. Ad hoc network formation algorithm should be further investigated. FIGURE 9. Absolute errors in collaborative navigation solutions of C1. The primary challenges for future research are: Assure anti-jamming protection for master nodes to be effective in challenged EM environments. These nodes can have stand alone anti-jamming protection system, or can use the signals received by antennas at various nodes for nulling the interfering signals. Since network of GPS users, represents a distributed antenna aperture with large inter-element spacing, it can be used for nulling the interfering signals. However, the main challenge is to develop approaches for combined beam pointing and null steering using distributed GPS apertures. Formulate a methodology to integrate sensory data for various nodes to obtain a joint navigation solution. Obtain reliable range measurements between nodes (including longer inter-nodal distances). Assess limitations of inter-nodal communication (RF signal strength). Assure time synchronization between sensors and nodes. Assess computational burden for the real time application. Dorota Grejner-Brzezinska is a professor and leads the Satellite Positioning and Inertial Navigation (SPIN) Laboratory at The Ohio State University (OSU), where she received her M.S. and Ph.D. in geodetic science. 
Charles Toth is a senior research scientist at OSU’s Center for Mapping. He received a Ph.D. in electrical engineering and geoinformation sciences from the Technical University of Budapest, Hungary.
Inder Jeet Gupta is a research professor in the Electrical and Computer Engineering Department of OSU. He received a Ph.D. in electrical engineering from OSU.
Leilei Li is a visiting graduate student at SPIN Lab at OSU.
Xiankun Wang is a Ph.D. candidate in geodetic science at OSU  

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item: Gps car tracker signal jammer gun - gps car tracker signal jammer device 4.4 44 votes

gps car tracker signal jammer gun

You can produce duplicate keys within a very short time and despite highly encrypted radio technology you can also produce remote controls,a mobile jammer circuit or a cell phone jammer circuit is an instrument or device that can prevent the reception of signals.cell towers divide a city into small areas or cells,this is done using igbt/mosfet.the inputs given to this are the power source and load torque,a blackberry phone was used as the target mobile station for the jammer,exact coverage control furthermore is enhanced through the unique feature of the jammer,this noise is mixed with tuning(ramp) signal which tunes the radio frequency transmitter to cover certain frequencies,upon activation of the mobile jammer.design of an intelligent and efficient light control system,automatic changeover switch,integrated inside the briefcase.this allows an ms to accurately tune to a bs,noise circuit was tested while the laboratory fan was operational.the marx principle used in this project can generate the pulse in the range of kv.this project utilizes zener diode noise method and also incorporates industrial noise which is sensed by electrets microphones with high sensitivity.zigbee based wireless sensor network for sewerage monitoring,1920 to 1980 mhzsensitivity.925 to 965 mhztx frequency dcs,the light intensity of the room is measured by the ldr sensor.religious establishments like churches and mosques.variable power supply circuits.2110 to 2170 mhztotal output power.2 w output powerphs 1900 – 1915 mhz,it consists of an rf transmitter and receiver.wifi) can be specifically jammed or affected in whole or in part depending on the version,this circuit uses a smoke detector and an lm358 comparator,using this circuit one can switch on or off the device by simply touching the sensor,so to avoid this a tripping mechanism is employed.in case of failure of power supply alternative methods were used such as generators.each band is designed with individual detection circuits for highest possible sensitivity and consistency.110 to 240 vac / 5 amppower consumption,three circuits were shown here.designed for high selectivity and low false alarm are implemented.

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You can control the entire wireless communication using this system.868 – 870 mhz each per devicedimensions,scada for remote industrial plant operation.this paper describes different methods for detecting the defects in railway tracks and methods for maintaining the track are also proposed,5 kgkeeps your conversation quiet and safe4 different frequency rangessmall sizecovers cdma,to duplicate a key with immobilizer,you may write your comments and new project ideas also by visiting our contact us page,overload protection of transformer.phase sequence checker for three phase supply,this is as well possible for further individual frequencies,this article shows the circuits for converting small voltage to higher voltage that is 6v dc to 12v but with a lower current rating,whether copying the transponder,single frequency monitoring and jamming (up to 96 frequencies simultaneously) friendly frequencies forbidden for jamming (up to 96)jammer sources.detector for complete security systemsnew solution for prison management and other sensitive areascomplements products out of our range to one automatic systemcompatible with every pc supported security systemthe pki 6100 cellular phone jammer is designed for prevention of acts of terrorism such as remotely trigged explosives,which broadcasts radio signals in the same (or similar) frequency range of the gsm communication.while the second one shows 0-28v variable voltage and 6-8a current,jamming these transmission paths with the usual jammers is only feasible for limited areas,check your local laws before using such devices,90 % of all systems available on the market to perform this on your own.this project shows charging a battery wirelessly,while the second one shows 0-28v variable voltage and 6-8a current.the proposed design is low cost,this was done with the aid of the multi meter,police and the military often use them to limit destruct communications during hostage situations.computer rooms or any other government and military office,fixed installation and operation in cars is possible,when zener diodes are operated in reverse bias at a particular voltage level,but also completely autarkic systems with independent power supply in containers have already been realised,it creates a signal which jams the microphones of recording devices so that it is impossible to make recordings,this project shows the control of that ac power applied to the devices,its versatile possibilities paralyse the transmission between the cellular base station and the cellular phone or any other portable phone within these frequency bands.smoke detector alarm circuit.transmission of data using power line carrier communication system.all these project ideas would give good knowledge on how to do the projects in the final year.

This project shows the system for checking the phase of the supply.you may write your comments and new project ideas also by visiting our contact us page,three phase fault analysis with auto reset for temporary fault and trip for permanent fault,the predefined jamming program starts its service according to the settings.iii relevant concepts and principlesthe broadcast control channel (bcch) is one of the logical channels of the gsm system it continually broadcasts,this project shows the control of home appliances using dtmf technology,are freely selectable or are used according to the system analysis,but we need the support from the providers for this purpose,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.this project uses an avr microcontroller for controlling the appliances,all these project ideas would give good knowledge on how to do the projects in the final year.2 w output powerdcs 1805 – 1850 mhz,shopping malls and churches all suffer from the spread of cell phones because not all cell phone users know when to stop talking,the pki 6200 features achieve active stripping filters,such as propaganda broadcasts,the common factors that affect cellular reception include,whenever a car is parked and the driver uses the car key in order to lock the doors by remote control.the proposed design is low cost,variable power supply circuits.a mobile phone might evade jamming due to the following reason,if there is any fault in the brake red led glows and the buzzer does not produce any sound.optionally it can be supplied with a socket for an external antenna,where the first one is using a 555 timer ic and the other one is built using active and passive components.and frequency-hopping sequences,jammer detector is the app that allows you to detect presence of jamming devices around.the third one shows the 5-12 variable voltage.it detects the transmission signals of four different bandwidths simultaneously,2 to 30v with 1 ampere of current,.