Xsens Technologies has completed the staged release of the new generation MTi and MTi-G, its miniature MEMS based Attitude and Heading Reference Systems (AHRS). With the latest developments (described below), the MTi and MTi-G can be used in applications where MEMS technology was not suitable before.

Breakthrough performance increase of miniature MEMS inertial sensing technology

Xsens Technologies has completed the staged release of the new generation MTi and MTi-G, its miniature MEMS based Attitude and Heading Reference Systems (AHRS). With the latest developments (described below), the MTi and MTi-G can be used in applications where MEMS technology was not suitable before.

The MTi is a miniature, gyro-enhanced Attitude and Heading Reference System (AHRS). Its internal low-power signal processor provides drift-free 3D orientation as well as calibrated 3D acceleration, 3D rate of turn, and 3D magnetic field data. The MTi-G includes an integrated GPS and static pressure sensor as well, which makes it better suitable for orientation measurement in situations with (long term) accelerations.

The release features enhanced algorithms which benefit optimally from the latest improvements of the sensor electronics. Improvements have been realized in the following areas:

Improved MTi and MTi-G sensor electronics

New gyroscopes result in higher accuracy, because of lower noise levels, improved bias stability and bias g-sensitivity.

Introduction
Xsens uses the latest sensors and components for its products, along with sophisticated sensor calibration algorithms. As a result, the MTi and MTi-G offer the maximum performance one can get out of current state of MEMS technology.

What’s new?
First of all, the MTi and MTi-G contain new MEMS gyroscopes which achieve 50% reduction in noise compared to the previous gyroscopes. As a result, the sensor fusion algorithm can rely longer on the gyroscopes for attitude/heading calculation. In addition, the bias stability and bias g-sensitivity have improved, which makes the orientation output more accurate and robust. The hardware improvements combined with the latest firmware result in an improved orientation performance. The improvements are particularly visible in challenging conditions such as long term accelerations, (very slow) rotations, or situations with magnetic disturbance.

Enhanced MTi sensor fusion algorithm

Higher performance in challenging environments, particularly in magnetically disturbed environments, dynamic accelerations, and (slow) rotations.

Introduction
The MTi is a low-cost AHRS and the major added-value is the sensor fusion algorithm which gives attitude and heading. Because the attitude/heading estimation performance is heavily dependent on the assumed dynamics, Xsens offers several predefined set of filter settings to cater to a variety of applications.

What’s new?
The new sensor fusion algorithm offers major improvements especially for the following challenging situations:

1) Magnetic disturbed environments

Several features were added such as velocity dependence of the heading and a close assessment of the gyroscope vs. magnetometer output. These two features significantly improve magnetic immunity.

Figure 1 shows this improved magnetic immunity: the accuracy of the heading output has improved significantly compared to the MTi version before April 2008.

Figure 1: Heading error experienced in a magnetically disturbed environment for the MTi version before April 2008 (blue) compared to latest MTi Nov 2008 edition (red). The yaw (heading) angles were compared to a Fiber Optic Gyro (FOG) reference. Dynamic movements were made close to objects with large iron content.

Figure 2: RMS error values of both MTi versions within a strong magnetic environment shown in figure 1. The RMS value improved significantly.

2) Dynamic conditions

The new hardware combined with the latest firmware result in an improved orientation performance. This is especially visible under challenging conditions such as (asymmetrical) periodic accelerations and (very slow) rotations. The dynamic accuracy has now reached sub-degree RMS values.

The graphs in Figures 3 to 5 show the test results for dynamic conditions. The roll and pitch values are shown compared to a FOG (Fiber Optic Gyro) reference. The movements included dynamic accelerations, long-term accelerations in one direction, and rotations.

Figure 3: Test movements for the MTi, including highly dynamic 3D acceleration and rate-of-turn.

Figure 4: Roll and pitch of MTi and FOG reference, for test movements included highly dynamic 3D acceleration and rate-of-turn (see Fig. 3).

Figure 5: Roll and pitch error relative to FOG reference for the test movements shown in Fig. 3. The performance has clearly improved during periods of dynamic accelerations and rotations compared to the MTi version before April. 2008.

Figure 6: RMS error values for Roll (error relative to FOG reference). Test movements included highly dynamic 3D acceleration and rate-of-turn (see Fig. 3).

Figure 7: RMS error values for Pitch (error relative to FOG reference). Test movements included highly dynamic 3D acceleration and rate-of-turn (see Fig. 3).

MTi-G: Improved accuracy and robustness under challenging environments for GPS reception.

Introduction
The MTi-G is a low-cost miniature MEMS AHRS which is designed to provide accurate attitude and heading data particularly in situations of long-term transient accelerations, which often occur in automotive and aerospace applications. The MTi-G provides, in real-time, the 3D orientation, 3D acceleration and 3D angular velocity, as well as 3D position and 3D velocity.

AHRS orientation estimates typically suffer from long-term transient accelerations. The MTi-G overcomes this problem by making use of GPS navigation solution to correctly estimate the vertical reference.

What’s new?
Apart from the hardware improvements mentioned in the previous section “Improved MTi and MTi-G sensor electronics”, the new MTi-G sensor fusion algorithm provides improved accuracy and robustness. This comes mainly as a result of making better use of GPS navigation solution and its accompanying error estimates. The benefits of the new algorithm can be seen especially in challenging environments for GPS (e.g. urban canyons).