Gps jammer with fan blower - gps jammer Williams Lake

By Hans-Georg Büsing, Ulrich Haak, and Peter Hecker Future safety-relevant driver assistant systems demand vehicle state estimations accurate enough to match the position within a road lane, which cannot be provided by standalone GPS. A promising approach to meet the requirements is the fusion of standalone or differential GNSS measurements with vehicle sensor data like odometers or accelerometers. To achieve deeper sensor integration, a software GNSS receiver was developed at the Institute of Flight Guidance (IFF) that is able to use dead reckoning sensors to support its signal acquisition. This article presents an approach to estimate the signal states during outages based on the tightly coupled vehicle state, which reduces the reacquisition time and significantly increases the signal availability. GNSS-based navigation is a key enabler for future advanced driver assistance systems (ADAS). Car manufacturers have identified automotive assistance systems as core devices to propose their uniqueness mainly in the luxury and upper-class market segments. While the precision and availability of loosely coupled single-frequency GPS navigation satisfies the requirements of typical route guidance systems, future automotive systems — especially those that enhance driving safety — are more demanding on positioning system performance. The Institute of Flight Guidance (IFF) of the Technische Universität, Braunschweig, Germany, is involved in two research projects evaluating the performance of unaided traditional GNSS receivers coupled with vehicle sensor measurements such as odometers in a tightly coupled architecture. Besides these involvements, the IFF has developed a general-purpose software-based GNSS receiver allowing full access to signal processing routines. The benefits of the tight sensor fusion are reliable state estimations even during total signal outages that are common in the automotive sector due to tunnels, parking decks, or urban canyons. In this architecture, the GNSS receiver works autonomously to deliver raw GNSS-measurements only. Additional knowledge provided by the vehicle sensors cannot be used to support the receiver in any way. Besides other beneficial aspects in the tracking channels, additional external knowledge about the vehicle state has the potential to reduce acquisition times and improve the measurement availability significantly. The Institute of Flight Guidance uses a software environment called “Automotive Data and Time-Triggered Framework” (ADTF) for research in the field of ADAS and automotive navigation. In this software framework, the overall system architecture is assembled with independent modules. These modules are implemented as libraries and loaded into ADTF. Data is exchanged via pins that are defined as public variables. The framework also attaches timestamps to the individual measurements and adds a data recording and playback functionality. From a general-purpose software GNSS receiver, presented at the ION GNSS 2010, we have derived an automotive-specific ADTF software receiver module. The software framework adds the flexibility to synchronously process measurements from vehicle sensors additionally to the IF data from the front end. This gives us the opportunity to aid signal processing in the software GNSS receiver with additional external sensors. For positioning, a tightly coupled positioning filter based on GPS raw data measurements and the rear-wheel odometers is implemented. The vehicle’s motion is modeled using a kinematic relationship between the vehicle sensors and the GNSS measurements. Based on the tightly coupled vehicle state estimation, an acquisition state is processed during signal outages that enables the software GNSS receiver to reacquire the satellite signal instantaneously with high precision. In this article, the constituent parts of the system are presented and the estimation of the acquisition state derived. The system was tested in an urban scenario, and the state estimations validated with the recorded measurements. System Architecture The software-defined GNSS receiver developed by the IFF was designed to process the computationally expensive signal correlation on an Nvidia graphics board using the vast parallel processing capability of graphics processing units (GPUs). With the use of common graphics boards, an entire receiver can be implemented on an ordinary PC, needing only a front-end to receive digital GNSS signals in an intermediate frequency (IF) band. For research in the field of vehicle state estimation, a derivate of the software receiver of the Institute of Flight Guidance has been implemented in the “Automotive Data and Time-Triggered Framework” (ADTF). The software is commonly used in the automotive industry for the development of ADAS. Figure 1 shows a typical system layout in ADTF. A central component of the framework is the ability to record and play back measurement data, which is indicated by the buttons on the left of the screenshot. Figure 1. System Architecture in ADTF. (Click to enlarge.) Within ADTF, the systems are assembled from modules that are shown as blocks within the graphical configuration editor. Standard modules such as the connection of common hardware are provided with the framework. Custom modules can be implemented in C++ by the user. Every module is implemented as a dynamic library (DLL) and interpreted by the framework. Modules can be featured with input and output pins. These pins are implemented by using specific data types from the framework. The communication and data exchange between the modules is handled via these pins. They can be connected by graphically drawing connector lines in the configuration editor. ADTF provides the user with classes for timing and threading. Processes can thereby be linked to the ADTF system time, which is especially important as the data replay can be slowed down or sped up for debugging. The instantaneous reacquisition algorithm is based on a traditional approach of tightly coupling GNSS raw data with vehicle sensor measurements. The fusion is based on a kinematic model following the Ackermann geometry establishing the relationship between the vehicle’s motion and the respective measurements. At each time step of an arriving measurement, the vehicle’s motion is predicted based on the last estimated state with an extended Kalman filter. The prediction is then corrected using either measurements from the vehicle sensors or GNSS raw measurements. The range and Doppler measurements are calculated in the tracking channels of the ADTF software GNSS receiver. The corrected vehicle state is then fed back into the kinematic model for the next update cycle. In case the GNSS signal is lost in a tracking channel, a virtual tracking channel is initialized with the last calculated channel states. The change in the channel output is then predicted utilizing the change in the vehicle state and the current evaluation of the ephemeris. The schematic implementation of the channel state prediction is shown in Figure 2. Figure 2. Schematic of Channel State Prediction. (Click to enlarge.) Signal State Estimation Using the tightly coupled architecture presented above, an estimated position and velocity can even be provided during total signal outages. Assuming that the last valid observation of a satellite signal is stored together with its respective time to and position, an estimation of the signal state (that is, Doppler frequency, code- and carrier-phase) based on the estimation of the vehicle state during the signal outage at time t1 can be used for an instantaneous signal reacquisition. Using the ephemeris data provided by the respective GPS satellite the range between a user position xu and the satellite xsv can be calculated using the following terms     (1) and (2) with |…| indicating the Euclidian distance. Therefore the change of the range can be obtained with equations (1) and (2): (3) Assuming an unbiased Gaussian error distribution of the measurements, the tightly coupled system provides an estimation of the covariance matrix of the vehicle state. Using only the submatrix (4) related to the vehicle position, the covariance of the user position along the line-of-sight to the satellite can be obtained with the Euclidean norm of the line-of-sight vector (5) and the law of error propagation: (6) Furthermore, using the law of error propagation, it can be shown that the variance of the change of range estimation in equation (3) is obtained by:    (7) With the last valid range measurement related to time to, the signal state at time t1 can be obtained for the pseudo-range PSR    (8) and the carrier phase Φ:     (9) The resulting variance of these estimations can by expressed by    (10) and    (11) respectively. The estimate of the Doppler and the related variance can be obtained analogous. Considering the variances of the estimation, it can be decided if the signal can be reacquired instantaneously or if the receiver has to find the signal using standard acquisition routines in a limited search space. Experimental Validation The Volkswagen Passat station wagon operated by the Institute of Flight Guidance was used to evaluate the performance of the proposed algorithm (see PHOTO.) The test vehicle is customized from the standard by adding an additional generator to meet the power requirements of the measurement and processing hardware. In addition, the Controller Area Network (CAN) is mirrored and open to access the data collected by the sensors of the vehicle. The relevant sensors include a longitudinal accelerometer, a gyro for measuring the yaw rate as well as the odometers of all four wheels. The test vehicle is equipped with a GNSS front-end developed by the Fraunhofer Institute for Integrated Circuits. It is capable of streaming L1, L2, and L5 RF samples via two USB ports. The sampling rate of L1 is 40.96 MHz at an intermediate frequency of 12.82 MHz. Test Vehicle. A customized Volkswagen Passat was used to evaluate performance of the algorithm. The vehicle sensor data is streamed via CAN to an automotive PC from Spectra. It is equipped with an Intel quadcore CPU, 8 GB RAM, a Vector PCI CAN device and 256 GB SATA solid state disk allowing up to 195 MB/s writing speed. Additionally, it has been equipped with an Nvidia GeForce GT 440 graphics board that is used for processing the GNSS RF data. This specific graphics board was chosen because it offers a comparably high performance of the GPU at relatively low power consumption. Both GNSS RF data and data from the vehicle sensor network are streamed to an ADTF hard disk recorder. Due to the setup of the data acquisition, several challenges have to be solved. The first challenge is that the front-end needs to be used as hardware-in-the-loop. It is by itself not equipped with an automated gain control. Therefore, it is not possible to just stream the RF data but it has to be decoded, processed for adjusting the gain, and then stored to the hard drive. Secondly, the recording setup needs to cover high data rates. The GNSS front-end streams approximately 20 MB/s. As the data needs to be decoded and processed for gain control, the expanded data rate for recording is ~40 MB/s. In total including vehicle sensor measurements, >2000 data packets per second are streamed to the recorder. Because this could not be done using mechanical hard drives, we used solid state disks that also allow data storage during times of high vibration. Related to the before-mentioned challenges, an efficient thread management needed to be implemented. The software framework’s threading classes are utilized to parallelize the receiver processes. Additionally, it has arisen that a significant part of the processing time is taken by the data transfer to the memory of the GPU. In order to prove the advantages of an odometer-aided reacquisition, an applicable testing scenario was chosen. To distinguish an odometer-based aquisition approach from a model-based approach, a trajectory was chosen that features a right turn of 90 degrees immediately after cutting off the GNSS signal. A model-based kinematic prediction would project the trajectory in the direction of the latest known heading derived by the GNSS solution. Only a sensor-based state estimation is able to resolve the right turn. The driven trajectory is shown in Figure 3. The GNSS signal has been cut off for approximately 10 seconds, which is equivalent of a 75-meter drive on dead reckoning sensors only after the right turn. Figure 3. Trajectory of test drive includes a 90-degree turn. (Click to enlarge.) Results The following plots in Figure 4 show the performance of the virtual tracking channels. The plots in the upper row show the pseudorange output over time. For vividness they have been corrected for the motion of the respective satellite that is dominant due to their high speeds. Over a short period of time the satellites’ motion relative to the receiver can be linearly approximated. The pseudorange measurements over time were fit using a linear regression. The respective value of the linear regression was then subtracted from the pseudorange and plot over time as shown in the figures in the second row, leaving only the approximated influence of the vehicle’s motion. Figure 4. Modified pseudorange and Doppler results of the virtual tracking channels. (Click to enlarge.) The Doppler measurements have been similarly compensated by just subtracting the minimum measurement. These modifications of the pseudorange and Doppler measurements allow a direct comparison of each other as the Doppler can be understood as the first derivate of the pseudorange over time. The results of PRN 6 show that the Doppler estimate during the GPS outage smoothly fits into the surrounding measurements without any major outliers. The plot of the pseudorange shows a similar behavior. The pseudorange could have potentially been modeled using a dynamic prediction that is not based on vehicle sensors due to the limited dynamics on the pseudorange measurements. The Doppler plot of PRN 16 shows a strong change in the relative velocity between satellite and receiver. If a further projection of the Doppler using a linear dynamic model would have been used instead of predicting with vehicle sensors, it would likely have misled the reacquisition by ~ 50 Hz. The trend in the pseudorange measurements is comparable to PRN 6 at a higher rate of change. The plots of PRN 21 probably show the advantages of using vehicle sensors for reacquisition best as the dynamics on pseudorange and Doppler are the most significant in the group. Both pseudorange and Doppler show a turning point during the GNSS outage. Especially, the pseudorange would have been mismodeled using a kinematic predicion that is not relying on additional sensors. Conclusion In this article, a tightly coupled positioning system implemented in the automotive-specific framework ADTF was presented that is based on the fusion of standard automotive sensor data and software receiver measurements. We showed that, using the tightly coupled solution, an acquisition state during signal outages can be estimated that allows the tracking channels to reacquire the signal instantaneously without the need of computationally expensive acquisition routines. Under the assumption of a tightly coupled RTK position and small outage times, a reacquisition of the carrier phase without loosing the information about the phase ambiguity seems possible. In the next version of the automotive GNSS receiver, the authors are planning to integrate the vehicle sensors to aid the tracking loops, which is likely to further improve tracking continuity especially in scenarios with high vegetation. Additionally, we plan to show that the implementation is capable of working in real time. Improvements of the initialization of the virtual tracking loops are also intended. Acknowledgments This article is based on a paper presented at ION-GNSS 2011, held September 19–23 in Portland, Oregon. This work was funded by the Federal State of Lower Saxony, Germany. Project: Galileo – Laboratory for the research airport Braunschweig. The authors would like to thank their colleagues working in the automotive navigation group for continuous support with the ADTF framework. Hans-Georg Büsing holds a Dipl.-Ing. in aerospace engineering from the Technische Universität Braunschweig and has been a research engineer at IFF since 2008. He works in the area of applied satellite navigation, especially in the field of vehicle positioning. Ulrich Haak holds a Dipl.-Ing. in mechanical engineering from the Technische Universität Braunschweig and joined IFF in 2008 as a research engineer. He works in the areas of receiver design and positioning algorithms. Peter Hecker joined IFF in 1989 as research scientist. Initial focus of his scientific work was in the field of automated situation assessment for flight guidance. From 2000 until 2005, he was head of the DLR Pilot Assistance department. Since April 2005, he has been director of IFF. He is managing research activities in the areas of air/ground cooperative air traffic management, airborne measurement technologies and services, satellite navigation, human factors in aviation, and safety in air transport systems.

gps jammer with fan blower

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Dve dsa-0051-05 fus 55050 ac adapter 5.5vdc .5a usb power supply.samsung atads10jbe ac adapter 5v dc 0.7a used usb pin cellphone,radioshack 273-1695 ac adapter 3,5,6,6.5vdc 2.5a digital camera.replacement ysu18090 ac adapter 9vdc 4a used -(+) 2.5x5.5x9mm 90,dve dsa-30w-05 us 050200 ac adapter+5v dc 4.0a used -(+) 1.3x3.here a single phase pwm inverter is proposed using 8051 microcontrollers,eng 3a-161wp05 ac adapter 5vdc 2.6a -(+) 2.5x5.5mm 100vac switch,lei mt12-y090100-a1 ac adapter 9vdc 1a used -(+) 2x5.5x9mm round,cf-aa1653a m2 ac adapter 15.6vdc 5a used 2.5 x 5.5 x 12.5mm.3g network jammer and bluetooth jammer area with unlimited distance.such as propaganda broadcasts,philips 4203 035 78410 ac adapter 1.6vdc 100ma used -(+) 0.7x2.3,ron gear rgd35-03006 ac adapter 3vdc 300ma used -(+) 0.15x2.5x10.this project shows the starting of an induction motor using scr firing and triggering.lac-cp19v 120w ac adapter 19v 6.3a replacement power supply comp,advent 35-12-200c ac dc adapter 12v 100ma power supply,pc-3010-dusn ac adapter 3vdc 1000ma used 90 degree right angle a.hp pa-1650-02hc ac adapter 18.5v 3.5a used 1x5 x7.5x12.8mm lapto.toshiba pa3507u-1aca ac adapter 15vdc 8a desktop power supply,energizer ch15mn-adp ac dc adapter 6v 4a battery charger power s.hitron hes49-12040 ac adapter 12vdc 4a (+)- 2.5x5.5mm 100-240vac.braun 4729 towercharger 100-130vac 2w class 2 power supply ac,wireless mobile battery charger circuit,buslink dsa-009f-07a ac adapter 7.5vdc 1.2a -(+) 1.2x3.5mm 100-2,here is the diy project showing speed control of the dc motor system using pwm through a pc,creative xkd-z1700 i c27.048w ac adapter 27vdc 1.7a used -(+) 2x,black & decker 143028-05 ac adapter 8.5vac 1.35amp used 3x14.3mm.d-link van90c-480b ac adapter 48vdc 1.45a -(+) 2x5.5mm 100-240va,hp compaq adp-65hb b ac adapter 18.5vdc 3.5a -(+) 1.7x4.8mm used,a mobile phone might evade jamming due to the following reason.but communication is prevented in a carefully targeted way on the desired bands or frequencies using an intelligent control,car adapter 7.5v dc 600ma for 12v system with negative chassis g,vehicle unit 25 x 25 x 5 cmoperating voltage.landia p48e ac adapter 12vac 48w used power supply plug in class,finecom jhs-e02ab02-w08b ac adapter 5v dc 12v 2a 6 pin mini din,but also completely autarkic systems with independent power supply in containers have already been realised,ads-1210pc ac adapter 12vdc 1a switching power supply 100 - 240v.spi sp036-rac ac adapter 12vdc 3a used 1.8x4.8mm 90° -(+)- 100-2.ksah2400200t1m2 ac adapter 24vdc 2a used -(+) 2.5x5.5mm round ba,90w-lt02 ac adapter 19vdc 4.74a replacement power supply laptop,netcom dv-9100 ac adapter 9vdc 100ma used -(+) 2.5x5.5mm straigh,rayovac ps6 ac adapter 14.5 vdc 4.5a class 2 power supply,xp power aed100us12 ac adapter 12vdc 8.33a used 2.5 x 5.4 x 12.3.mastercraft 5104-18-2(uc) 23v 600ma power supply,aqualities spu45e-105 ac adapter 12vdc 3a used 2 shielded wire.ad-1235-cs ac adapter 12vdc 350ma power supply.kodak mpa7701l ac adapter 24vdc 1.8a easyshare dock printer 6000,rayovac ps1 ac adapter 2vdc 200ma used battery cell power charge,the proposed design is low cost.viasat ad8530n3l ac adapter 30vdc 2.7a -(+) 2.5x5.5mm charger fo.apple usb charger for usb devices with usb i pod charger.kali linux network configuration with ip address and netmask.ryobi p113 class 2 battery charger 18v one+ lithium-ion batterie, ,an antenna radiates the jamming signal to space.it is efficient in blocking the transmission of signals from the phone networks.plantronics ssa-5w-05 0us 050018f ac adapter 5vdc 180ma used usb.ibm 02k7006 ac adapter 16vdc 3.36a used -(+)- 2.5x5.5mm 100-240v,sony bc-7f ni-cd battery charger,mw mws2465w-1 ac adapter 15-24vdc 63w used straight round barrel,motorola htn9000c class 2 radio battery charger used -(+) 18vdc.hp compaq ppp014h-s ac adapter 19vdc 4.74a used barrel with pin.sun fone actm-02 ac adapter 5vdc 2.5a used -(+)- 2 x 3.4 x 9.6 m,bti ac adapter used 3 x 6.3 x 10.6 mm straight round barrel batt.another big name in the cell phone signal booster market.

This sets the time for which the load is to be switched on/off,it captures those signals and boosts their power with a signal booster.the proposed system is capable of answering the calls through a pre-recorded voice message,energizer pl-7526 ac adapter6v dc 1a new -(+) 1.5x3.7x7.5mm 90.1800 mhzparalyses all kind of cellular and portable phones1 w output powerwireless hand-held transmitters are available for the most different applications.delta adp-12ub ac adapter 30vdc 0.4a dld010428 14d0300 power sup,ningbo dayu un-dc070200 ac adapter used 7.2vdc 200ma nicd nimh b.recoton adf1600 voltage converter 1600w 500watts.compaq 340754-001 ac adapter 10vdc 2.5a used - ---c--- + 305 306.12v car charger auto cigrate lighter 1.5x4mm round barrel,finecom thx-005200kb ac adapter 5vdc 2a -(+)- 0.7x2.5mm switchin.microsoft 1040 used receiver 1.0a for media center pc with windo,sceptre ad1805b 5vdc 3.7a used 3pin mini din ite power supply.with infrared the remote control turns on/off the power,ibm pscv540101a ac adapter 12v 4.5v used 4.4 x 5.8 x 10.3mm roun.ibm adp-160ab ac adapter 12vdc 13.33a 6pin molex power supply.panasonic pv-dac13 battery charger video camera ac adapter,dell pa-1600-06d2 ac adapter 19v dc 3.16a 60w -(+)- used 3x5mm,by this wide band jamming the car will remain unlocked so that governmental authorities can enter and inspect its interior.hipower a0105-225 ac adapter 16vdc 3.8a used -(+)- 1 x 4.5 x 6 x,the marx principle used in this project can generate the pulse in the range of kv.the jamming radius is up to 15 meters or 50 ft,ac 110-240 v / 50-60 hz or dc 20 – 28 v / 35-40 ahdimensions,d-link mu05-p050100-a1 ac adapter 5vdc 1a used -(+) 90° 2x5.5mm.zyxel a48091000 ac adapter 9v 1000ma used 3pin female class 2 tr,uniden ac6248 ac adapter 9v dc 350ma 6w linear regulated power s,technology private limited - offering jammer free device.clean probes were used and the time and voltage divisions were properly set to ensure the required output signal was visible,ad-1820 ac adapter 18vdc 200ma used 2.5x5.5x12mm -(+)-.dv-1215a-1 ac adapter 9v 1.5a 30w ae-980 power supplycondition,texas instruments xbox 5.1 surround sound system only no any thi,the predefined jamming program starts its service according to the settings,archer 273-1651 ac adapter 9vdc 500ma used +(-) 2x5x12mm round b.deer ad1812g ac adapter 10 13.5vdc 1.8a -(+)- 2x5.5mm 90° power,hp photosmart r-series dock fclsd-0401 ac adapter used 3.3vdc 25,toshiba pa3673e-1ac3 ac adapter 19v dc 12.2a 4 pin power supply.makita dc1410 used class 2 high capacity battery charger 24-9.6v,completely autarkic and mobile.traders with mobile phone jammer prices for buying,radioshack ni-cd ni-mh 1 hr battery charger used 5.6vdc 900ma 23,zigbee based wireless sensor network for sewerage monitoring,yd-001 ac adapter 5vdc 2a new 2.3x5.3x9mm straight round barrel.by activating the pki 6100 jammer any incoming calls will be blocked and calls in progress will be cut off,acbel api3ad14 ac adapter 19vdc 6.3a used (: :) female 4pin fema.aps aps48ea-114 ac dc adapter 7.5v 1.5a power supply,your own and desired communication is thus still possible without problems while unwanted emissions are jammed,cobra swd120010021u ac adapter 12vdc 100ma used 2 audio pin.by the time you hear the warning.sino-american sa120g-05v ac adapter 5vdc 4a used +(:_:)- 4 pin 9,gemini dcu090050 ac adapter 9vdc 500ma used -(+)- 2.5x5.4mm stra,eng 3a-152du15 ac adapter 15vdc 1a -(+) 1.5x4.7mm ite power supp,shenzhen jhs-q05/12-s334 ac adapter 12vdc 5v 2a s15 34w power su.phihong psaa15w-240 ac adapter 24v 0.625a switching power supply,incoming calls are blocked as if the mobile phone were off.finecom azs9039 aa-060b-2 ac adapter 12vac 5a 2pin din ~[ o | ]~,tpi tsa1-050120wa5 ac dc adapter 5v 1.2a charger class 2 power s,soft starter for 3 phase induction motor using microcontroller,dell 24111 ac dc adapter 12v 2a power supply,3com sc102ta1203f02 ac adapter 12vdc 1.5a used 2.5x5.4x9.5mm -(+.if you find your signal is weaker than you'd like while driving.finecom bc12v5a-cp ac charger 12vdc 5a replacement power supply.v-2833 2.8vdc 165ma class 2 battery charger used 120vac 60hz 5w.two way communication jammer free devices,coleman cs-1203500 ac adapter 12vdc 3.5a used -(+) 2x5.5x10mm ro,dell adp-50sb ac adapter 19vdc 2.64a 2pin laptop power supply.

Fujitsu seb100p2-19.0 ac adapter 19vdc 4.22a -(+) used 2.5x5.5mm,cal-comp r1613 ac dc adapter 30v 400ma power supply,lg lcap16a-a ac adapter 19vdc 1.7a used -(+) 5.5x8mm 90° round b.pelouze dc90100 adpt2 ac adapter 9vdc 100ma 3.5mm mono power sup,514 ac adapter 5vdc 140ma -(+) used 2.5 x 5.5 x 12mm straight ro.gft gfp241da-1220 ac adapter 12vdc 2a used 2x5.5mm -(+)- 100-240,condor hk-b520-a05 ac adapter 5vdc 4a used -(+)- 1.2x3.5mm,sony vgp-ac19v10 ac dc adapter 19.5v 4.7a power supply adp-90yb.fujitsu adp-80nb a ac adapter 19vdc 4.22a used -(+) 2.5x5.5mm c,ibm 12j1441 ac adapter 16vdc 2.2a class 2 power supply 12j1442,cell phone jammer is an electronic device that blocks transmission of ….radio remote controls (remote detonation devices),casio ad-c59200j ac adapter 5.9v dc 2a charger power supply,.