Taking aim with MEMS gyros

Examine smartphones and advanced video-game consoles and you’ll find MEMS gyroscopes giving feedback for a variety of tasks involving orientation and position. Yet the MEMS devices in these consumer products fall short for a number of industrial uses where the gyroscope sees conditions much rougher than those characterizing living rooms or the pocket of a cell-phone user.

Full 3D motion-sensing applications require a combination of accelerometers, gyroscopes, compasses and pressure sensors. Accelerometers measure linear acceleration along the X, Y or Z axis, and can be used to measure gravitational acceleration. They have served for many years in products such as automotive air bags and PC notebook disk-drive fall-protection systems. Compasses sense the earth’s magnetic field to provide an absolute heading. Pressure sensors measure atmospheric pressure and can be used to determine altitude. Gyroscopes measure rotational motion around the X, Y and Z axis and are used for applications such as stability-control systems in aircraft, stabilization systems for satellite receivers, and to augment GPS navigation systems.

A wide range of industrial applications now need MEMS gyroscopes. These industrial-grade MEMS sensors differ from consumer-grade devices in that they can accurately perform in harsh conditions characterized by extreme temperature ranges, despite shocks and constant vibrations. But industrial-grade gyroscopes also tend to be costly and bulky. The typical way of making an industrialgrade multiaxis gyroscope has been to combine discrete single-axis packages. This approach has entailed a significant integration effort and forced developers to have more system-level expertise than when working with consumergrade devices. But this situation has changed with the introduction of industrial gyroscopes that employ MEMS technology to handle multiple axes.

Industrial applications for motion sensing include platform stabilization, land, air, sea, and space navigation systems, precision agriculture, precision robotics, unmanned aerial (UAV) and nautical vehicles, construction equipment, offshore drilling, borehole survey, and handheld inventory-control systems to name just a few.

Industrial applications have different needs than the consumer space. Specifically, there are four basic areas where an industrial gyroscope must outperform a consumer- grade gyroscope: temperature range, bias instability, noise, and vibration performance while maintaining small form factor and low cost.

In agriculture, for example, farmers must maximize crop yields. One pass of a tractor through a field must align with the next to within a few centimeters. The task requires use of a precision gyroscope able to accurately measure the tractor heading despite vibrations from moving machinery, heat from its engine and the environment, and location noise from the uneven ground. Marine-based satellite antenna stabilization is another good example, where a boat must constantly communicate with a satellite. Industrial-grade gyroscopes counterbalance boat motion caused by the oscillation of the waves. Additionally, the gyroscope must overcome noise from smaller waves and the vibration of the boat engine all while maintaining accuracy over the long term.

There are different types of gyroscopes, but MEMS devices are generally preferred because of their high performance, affordability, and small size. Industrial-grade MEMS gyroscopes can overcome extreme environmental conditions and can address the need for better bias instability, a wider temperature range, and better noise and vibration rejection.

Bias instability

The bias of a gyroscope is its output in no-rotation mode. Bias instability is how the bias changes over time at a constant temperature. While a gyroscope’s constant bias could potentially be calibrated out, bias instability introduces an error that may not be easy to calibrate. This is why bias instability is important when selecting a gyroscope. The longer a gyroscope operates, the greater its bias error. So a low bias error is critical for applications that need excellent accuracy over long periods.

Bias instability is measured in terms of the standard deviation of the gyro output averaged over fixed blocks of time. The typical approach is to plot these standard deviations for different sizes of blocks of time versus the sizes of the corresponding blocks of time. This generates what is called an Allan Variance plot. The minimum point on the curve designates the gyroscope’s bias instability value, the greatest stability the gyroscope can achieve. The lower this value, the better the bias performance. A gyroscope with a lower Allan Variance curve performs better than a gyroscope with a higher Allan Variance curve.

The accompanying figure shows a bias instability as low as 15°/hr for an industrial gyroscope from InvenSense, Sunnyvale, Calif. It is a three-axis device that measures the rotation rate in the X, Y, and Z directions.

Another important measure of performance is the noise that the gyroscope exhibits. At short averaging times (horizontal axis of the Allan Variance plot), sensor noise dominates the Allan Variance. A measure of gyroscope- noise performance, known as Angle Random Walk (ARW), can be obtained from the Allan Variance value at the 1-sec crossing time. It is measured at 1 sec so it can be multiplied by any time value, t, to obtain the noise contribution of the orientation error at that value of t. For example, if t = 100 sec and ARW = 0.2°/√sec, the noise contribution of the orientation error over a period of 100 sec would be 0.2 × (√100) = 2°.

There can be a large noise variation among the various industrial gyroscope vendors, so designers typically pay extra attention to this parameter. To see why, consider a precision robotics application where the robot attaches a windshield to a car. The glass must accurately align to the car frame. Too much gyroscope noise may not give the required accuracy, resulting in a poorly installed windshield.

Temperature and vibration

Industrial applications generally entail a –40 to 105°C temperature range versus the –40 to 85°C range for consumer- grade devices. Gyroscope qualities degrade over temperature, so the challenge for gyroscope manufacturers is in ensuring all characteristics stay within a reasonable range. Parameters sensitive to temperature include bias instability, noise, and sensitivity. System integrators should characterize all these parameters over temperature to confirm performance will meet system targets.

Vibration performance can be important in many industrial applications. And it can be challenging to ensure a gyroscope performs accurately in the presence of a humming motor or similar noise sources. Consider the example of a gyroscope on a tractor with a motor that vibrates the chassis where the rate of vibration varies with the rate at which the operator revs the engine. This vibration can be modeled as noise in the gyroscope output, possibly resulting in inaccuracies that are too large to accommodate. To address the issue, the designer can improve the performance by locating the gyroscope in a spot where vibrations are dampened (e.g., within the tractor cab). But in general, it’s better not to be forced into limiting where the gyroscope can go. Other design considerations, such as aggressive antialias and decimation filtering, can help minimize vibration issues. But the less sensitive the gyroscope is to vibration, the less aggressive these filters need to be.

Device accuracy is important but highly accurate devices don’t necessarily guarantee a highly accurate motion sensing system. Many modern industrial gyroscopes have been restricted to one or two axes. Thus, they have had to be combined when needs called for three axes. This requires a precise 90° alignment on a PCB. Otherwise, crossaxis alignment errors propagate to the final representation of the motion. To minimize the cross-axis errors, developers must implement system-level calibration routines.

In contrast, a single-chip three-axis MEMS gyroscope is calibrated during its manufacture to cancel out all crossaxis errors. This eliminates a calibration step for system integrators. And, of course, a single-chip three-axis gyroscope will be much smaller than a multichip solution.

© 2012 Penton Media, Inc.