Integrated Inertial/gps

The presence of failures in navigation sensors can cause the determination of an erroneous aircraft state estimate, which includes position, attitude, and their derivatives. Aircraft flight control systems rely on sensor inputs to determine the aircraft state. In the case of integrated Inertial/NAVSTAR Global Positioning System (GPS), sensor failures could occur in the on-board inertial sensors or in the GPS measurements. The synergistic use of both GPS and the Inertial Navigation System (INS) allows for highly reliable fault detection and isolation of sensor failures. Integrated Inertial/GPS is a promising technology for the High Speed Civil Transport (HSCT) and the return and landing of a manned space vehicle

An Effective Multi-Cue Positioning System for Agricultural Robotics

The self-localization capability is a crucial component for Unmanned Ground Vehicles (UGV) in farming applications. Approaches based solely on visual cues or on low-cost GPS are easily prone to fail in such scenarios. In this paper, we present a robust and accurate 3D global pose estimation framework, designed to take full advantage of heterogeneous sensory data. By modeling the pose estimation problem as a pose graph optimization, our approach simultaneously mitigates the cumulative drift introduced by motion estimation systems (wheel odometry, visual odometry, ...), and the noise introduced by raw GPS readings. Along with a suitable motion model, our system also integrates two additional types of constraints: (i) a Digital Elevation Model and (ii) a Markov Random Field assumption. We demonstrate how using these additional cues substantially reduces the error along the altitude axis and, moreover, how this benefit spreads to the other components of the state. We report exhaustive experiments combining several sensor setups, showing accuracy improvements ranging from 37% to 76% with respect to the exclusive use of a GPS sensor. We show that our approach provides accurate results even if the GPS unexpectedly changes positioning mode. The code of our system along with the acquired datasets are released with this paper.Comment: Accepted for publication in IEEE Robotics and Automation Letters, 201

Comparative evaluation of various GPS-free localization algorithm for wireless sensor networks

Wireless Sensor Networks (WSN) are tremendously being used in different environments to perform various monitoring tasks such as search, rescue, disaster relief, target tracking and a number of tasks in smart environments. For example wireless sensors nodes can be designed to detect the ground vibrations generated by silent footsteps of a burglar and trigger an alarm. In many difficult and complex tasks, node localization is very important and critical step to fulfill the purpose of WSN. This project was conducted on the basis of localization of sensor nodes in the scope of GPS-free localizations schemes. We firstly investigated the current localization techniques in wireless scenario for the aim of designing a GPS-free localization scheme based on the local coordinate system formation. A multidimensional scaling method based on dynamic curvilinear belt structure and cooperative localization method was used in this project. Then a simulation result and comparison were carried in MATLAB. The vast majority of current materials on spot discovery in WSNs reflect some beacon nodes with known place. Their spots are then used to look for the positions connected with other normal sensor nodes. Manual rating and configuration means of obtaining spot don't scale and are also error-prone, and equipping sensors with GPS is normally expensive and rule isn't followed in indoor and urban environment. As such, sensor sites can therefore gain from a selfsetting up method where nodes cooperate with each other, estimate nearby distances on their neighbors, and converge to some consistent organize system containing only translation freedom. Dis

Hardware Implementation of the GPS authentication

In this paper, we explore new area/throughput trade- offs for the Girault, Poupard and Stern authentication protocol (GPS). This authentication protocol was selected in the NESSIE competition and is even part of the standard ISO/IEC 9798. The originality of our work comes from the fact that we exploit a fixed key to increase the throughput. It leads us to implement GPS using the Chapman constant multiplier. This parallel implementation is 40 times faster but 10 times bigger than the reference serial one. We propose to serialize this multiplier to reduce its area at the cost of lower throughput. Our hybrid Chapman's multiplier is 8 times faster but only twice bigger than the reference. Results presented here allow designers to adapt the performance of GPS authentication to their hardware resources. The complete GPS prover side is also integrated in the network stack of the PowWow sensor which contains an Actel IGLOO AGL250 FPGA as a proof of concept.Comment: ReConFig - International Conference on ReConFigurable Computing and FPGAs (2012

Sistem Monitoring Sudut Hadap Payload Terhadap Titik Peluncuran Roket

Payload atau muatan roket merupakan salah satu produk elektronika yang sangat bermanfaat dalam bidang teknologi dirgantara. Payload tersusun atas beberapa sensor yang berfungsi untuk mengetahui keadaan lingkungan. Selain itu payload juga dibekali sensor-sensor yang digunakan sebagai monitor pergerakan payload. Sensor kompas digital merupakan salah satu sensor yang digunakan untuk menunjukkan arah payload. Sedangkan modul GPS merupakan modul yang dapat menunjukkan koordinat titik peluncuran serta posisi payload saat bergerak di udara. Sensor kompas digital CMPS10 dan modul GPS SKM-53 dapat diimplementasikan pada payload sehingga dapat menunjukkan sudut hadap payload terhadap titik peluncurannya. Hasil pengujian menunjukan bahwa modul kompas digital CMPS10 memiliki akurasi sebesar +1°. Modul GPS receiver SKM-53 memiliki akurasi sebesar 6,63 meter (radius). Modul RF transceiver YS-1020 mampu melakukan transmisi data hingga radius 270 meter. Sistem monitoring sudut hadap payload terhadap titik peluncuran mampu menunjukkan besarnya sudut hadap dengan akurasi sebesar 1° pada jarak lebih dari 50 meter, dan akurasi berubah hingga 15° pada jarak kurang dari 50 meter. Kata Kunci— Kompas Digital CMPS10, Modul GPS SKM-53, Sudut Hadap Payload

Search for transient ultralight dark matter signatures with networks of precision measurement devices using a Bayesian statistics method

We analyze the prospects of employing a distributed global network of precision measurement devices as a dark matter and exotic physics observatory. In particular, we consider the atomic clocks of the Global Positioning System (GPS), consisting of a constellation of 32 medium-Earth orbit satellites equipped with either Cs or Rb microwave clocks and a number of Earth-based receiver stations, some of which employ highly-stable H-maser atomic clocks. High-accuracy timing data is available for almost two decades. By analyzing the satellite and terrestrial atomic clock data, it is possible to search for transient signatures of exotic physics, such as "clumpy" dark matter and dark energy, effectively transforming the GPS constellation into a 50,000km aperture sensor array. Here we characterize the noise of the GPS satellite atomic clocks, describe the search method based on Bayesian statistics, and test the method using simulated clock data. We present the projected discovery reach using our method, and demonstrate that it can surpass the existing constrains by several order of magnitude for certain models. Our method is not limited in scope to GPS or atomic clock networks, and can also be applied to other networks of precision measurement devices.Comment: See also Supplementary Information located in ancillary file

Robust Gaussian Filtering using a Pseudo Measurement

Many sensors, such as range, sonar, radar, GPS and visual devices, produce measurements which are contaminated by outliers. This problem can be addressed by using fat-tailed sensor models, which account for the possibility of outliers. Unfortunately, all estimation algorithms belonging to the family of Gaussian filters (such as the widely-used extended Kalman filter and unscented Kalman filter) are inherently incompatible with such fat-tailed sensor models. The contribution of this paper is to show that any Gaussian filter can be made compatible with fat-tailed sensor models by applying one simple change: Instead of filtering with the physical measurement, we propose to filter with a pseudo measurement obtained by applying a feature function to the physical measurement. We derive such a feature function which is optimal under some conditions. Simulation results show that the proposed method can effectively handle measurement outliers and allows for robust filtering in both linear and nonlinear systems