MEMS inertial and Multi-GNSS test system to enable testing of sensor fusion algorithms.

SimSENSOR enables the controlled and progressive testing of sensor fusion algorithms for the integration and optimisation of Multi-GNSS and MEMS inertial sensors.

It extends the capabilities of Spirent’s GSS6700 or GSS8000 simulators by simulating MEMS sensor outputs on a common trajectory with the simulated GNSS signals.

Brochures

SimSENSOR enables you to:

• Test sensor fusion algorithms under a range of representative, controlled, repeatable conditions
• Simulate MEMS sensor noise effects
• Control sensor noise, and errors such as bias and drift
• Validate and optimise algorithm parameters
• Test in tightly or loosely coupled sensor fusion architectures

Sensor Fusion: More Accurate, More Available

Many location-aware devices now combine the strengths of multiple navigation technologies to deliver enhanced availability and improved accuracy, in environments where GNSS coverage is limited or denied.
Inertial navigation sensors are a great complement to technologies such as GNSS, cell-tower positioning and Wi-Fi positioning. Generically, their strengths and weaknesses are complementary: inertial keeps working when GNSS or other positioning technologies are denied or weak; GNSS or Wi-Fi positioning can be used to re-calibrate the cumulative drift of inertial sensors.

Controlled, Repeatable Testing

While the benefits of combining inertial and GNSS technologies are clear, performance testing sensor fusion algorithms during R&D raises a number of challenges, including the need to account for MEMS sensor noise and bias/drift errors.

Testing the performance of sensor fusion algorithms in the field can be particularly problematic. Such tests lack environmental control and repeatability, and are inherently expensive, slow and limited, generally relying on the construction of a physical moving platform.

SimSENSOR enables core algorithm testing in the lab by presenting Multi-GNSS and simulated MEMS sensor outputs to the bench environment. It simulates the output of four key MEMS sensors commonly included in location-aware devices:

• Accelerometers
• Gyroscopes
• Magnetometers
• Barometers

The simulated MEMS sensor outputs include representative noise and error (bias/drift), and SimSENSOR also provides trajectories that include representative human motion gestures.