Mini itx embedded low power emulator build

The calculated navigation states ( i.e., position, velocity and attitude) drift with time due to the needed integrations and the sensors errors (such as biases, scale factors, and noise) which lead to unbounded accumulation of errors. Measurements are integrated twice for accelerometers and once for gyroscopes to yield position and attitude.

The IMU consists of a triad of accelerometers and a triad of gyroscopes. The Inertial Navigation System (INS) is a sensor-based, self-contained, dead-reckoning navigation system in which measurements at a high sample rate, provided by an inertial measurement unit (IMU) are used by a navigation processor to compute the position, velocity and attitude of the moving object relative to a known starting position, velocity and attitude. Due to the mentioned reasons, GPS canвЂ™t provide a continuous and reliable solution when used as a stand-alone navigation system, and a better navigation solution can be obtained by integrating the measurements from one or more sensor-based systems, with GPS measurements. Signal interruption is one of the main reasons that affects the continuity and reliability of the GPS navigation solution. In urban canyons, tunnels, and other GPS-denied environments, the LOS requirement canвЂ™t be always met, resulting in GPS outages caused by GPS signal blockage, interference, jamming and multi-path effects. As a satellite-based navigation system, GPS requires a line-of-sight (LOS) between the receiverвЂ™s antenna and the satellites. Although, the navigation solution that is provided by GPS is sufficiently accurate, in the order of meters to centimeters, especially when augmented with other satellite-based or ground-based augmentation systems, it is unable to fulfill the requirements of continuity and reliability in some situations. The Global Positioning System (GPS) is a satellite-based, absolute-positioning navigation system, developed by the US Department of Defense (DoD) in the early 1970s, used to provide time, position and velocity information. Navigation is the science which comprises the methods and technologies to determine the time varying position, velocity and attitude of a moving object by utilizing either sensor-based or satellite-based measurements or by integrating the measurements from both navigation systems. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels.

Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. Additional features include integrated Intel graphics accelerator with HDMI, DVI-I and LVDS interfaces that support 3 displays: HDMI and DVI-I support up to 1920 x 1200 60Hz resolution, and LVDS supports 24-bit dual channel display.Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. The 4th generation Intel CoreTM processors with LGA 1150 socket enables smooth flash playback and rich 2D/3D graphics with high quality playback, providing a compelling visual experience for intelligent systems that display videos, graphics and interactive content such as digital signs.Дue to the Intel HD Graphics engine integrated into these 4th generation Intel Core processors, support is provided for 20 Graphics Execution Units (EUs) with dynamic turbo boost to accelerate video processing, and Intel Clear Video Technology providing advanced imaging capabilities for Blu-Ray and other high definition video processing. Providing low-power consumption and higher performance, the HD100-H81 is powered by the 4th generation Intel CoreTM processor family. DFI has added to its Intel H81 product line with the introduction of the HD100-H81, a new Mini-ITX embedded motherboard.

Mini itx embedded low power emulator build