Technology- Inertial Systems
MEMSIC is a leading supplier of solid-state Inertial Sensors and Systems for aerospace, commercial, automotive and industrial applications, with products used in over 600 different types of aircraft. MEMSIC’s cost-effective solutions provide a unique combination of performance and features through the packaging and integration of high-grade MEMS gyros and accelerometers, GPS technology and advanced DSP algorithms. MEMSIC’s Inertial Sensors and Systems are ideally suited for control, instrumentation and navigation in airborne, land and marine environments.
MEMSIC has been at the forefront of MEMS technology for more than a decade, and has developed an extensive and growing international customer base with more than 10,000 installations worldwide.
MEMSIC developed one of the first successful MEMS-based FAA-certified Attitude & Heading Reference Systems (AHRS), and continues to push the envelope with class-leading performance, design and technology for a vast array of applications including general aviation, commercial and military markets.
- Rugged reliability (MTBF>30,000 hours)
- price/performance ratio enabling wide use of applications
- small footprint
- user support/tools
Micro Electro Mechanical Systems (MEMS) technology has enabled the development of highly-reliable solid-state inertial sensors and systems for use in a wide variety of static and dynamic motion measurement applications. MEMS inertial sensors and systems are based on micro-machined silicon structures that are designed to detect the linear and/or angular motions of a freely moving body using the principles of inertia.
These chip-level silicon structures contain no moving parts, offer extremely low power and high reliability, and exhibit low sensitivity to vibration and shock. As a result of these key features, MEMS inertial sensors are ideally suited to a wide variety of applications, and provide a significant size, weight and cost advantage over the more traditional mechanical and fiber optic inertial technologies.
MEMSIC’s Inertial Systems incorporate an extended Kalman filter (EKF) algorithm that provides on-the-fly calibration of the angular rate sensors and linear accelerometers. The EKF algorithm uses feedback from the accelerometers, rate sensors, magnetometers and GPS (or air speed) to estimate corrections to the trajectory state and inertial sensor errors. The ability to accurately and effectively estimate these corrections and errors allows MEMSIC’s inertial systems to offer unparalleled performance and affordability.
The Kalman filter attitude correction approach achieves improved system performance as a result of its ability to estimate the attitude errors and gyro bias states. The advantage of this approach is that an absolute attitude error estimate is provided to the trajectory to correct any errors due to physical noise disturbances and gyro errors, as well as a characterization and tracking of the gyro biases, which in effect provides an online rate sensor calibration.
MEMSIC has developed and patented its EKF during the past 10 years, with several patents awarded for EKF use within inertial systems. As a part of its ongoing product improvement process, MEMSIC continues to extend and optimize its algorithms for more and more complex operating environments.
Inertial Systems are multi-axis sensor packages that measure the inertial forces experienced by the movement of an object in free space. The most frequent applications for inertial systems are navigation, attitude measurement and platform stabilization.
MEMSIC offers a wide range of inertial products that are based on the combination of MEMS acceleration and angular rate sensor technologies. The more highly integrated MEMSIC systems incorporate reference data from sources such as a three-axis magnetometer, GPS receiver or air data computer to enhance overall functionality and performance, however, all of MEMSIC’s inertial systems are designed to operate without the need for external aiding.
Accurate attitude sensing is accomplished by measuring acceleration in three orthogonal axes and by measuring angular rate about each of these axes to compute Roll and Pitch angles relative to the gravity vector. Heading is calculated by computing the yaw angle about the z-axis relative to the earth’s magnetic field vector. The integration of GPS and/or airspeed (from air data computer) provides additional information for the Kalman filter, allowing it to provide better corrections for attitude determination, as well as the ability to estimate further accelerometer and magnetometer sensor errors including bias, scale factor and misalignment.