Obsidian Inertial Navigation System (IMU+GNSS positioning system)
Obsidian Inertial Navigation System (IMU+GNSS positioning system)
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$5,000.00 USD
Regular price
Sale price
$5,000.00 USD
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This device is a multifunctional sensor that merges two main components: An Inertial Measurement Unit (IMU) that has a 3 axis accelerometer and a 3 axis gyroscope. The accelerometer measures...
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Description
This device is a multifunctional sensor that merges two main components:
- An Inertial Measurement Unit (IMU) that has a 3 axis accelerometer and a 3 axis gyroscope. The accelerometer measures changes in velocity along three perpendicular axes (x, y, and z), and the gyroscope detects changes in rotational position (pitch, roll, and yaw) along the same axes.
- A Global Navigation Satellite System (GNSS) receiver, which communicates with satellites to determine the sensor’s location on Earth.
- 200Hz 32-bit Position (Latitude, Longitude, Altitude)
- 400Hz 32-bit Velocity (Body X, Body Y, Body Z, and 2D Speed)
- 400Hz 32-bit Body Frame Acceleration (Gravity Removed) (X, Y, Z) with online acceleration bias compensation
- 400Hz 32-bit Angular Rate (X, Y, Z) with online gyro bias compensation
- 400Hz 16-bit Orientation (Roll, Pitch, Yaw (Degrees))
- 100Hz “MoTeC GPS” simulation option for integration with MoTeC M1 ECU applications with locked firmware (GT-R, Lamborghini, etc…)
- CNC aluminum enclosure with Deutsch ASL connection
What makes this sensor unique is its onboard sensor fusion algorithm. This sophisticated software combines the different measurements from the IMU and the GNSS to produce very accurate and fast updates on the sensor’s position, orientation, and movement.
The sensor fusion algorithm also corrects for biases (systematic errors) in the accelerometer and gyroscope measurements, ensuring even more accurate data.
Moreover, the device can calculate the velocities in the sensor’s (or the vehicle’s) own frame of reference, which can be extremely useful for understanding and controlling its movement.
Purpose:
- The main objective with this sensor is to put cutting edge, high performance sensor fusion algorithms into the hands of motorsport integrators and motorsport engineers without having to deal with sensor calibration, embedded systems, or understanding the sensitivity of MEMS IMU’s, specifically.
Functional Overview:
- The sensor fusion algorithm that runs on this sensor is an Extended Kalman Filter (EKF). An EKF is a filter that combines data from multiple sensors and provides a best guess estimate of the position, orientation, and velocity of the vehicle.
This device is a multifunctional sensor that merges two main components:
- An Inertial Measurement Unit (IMU) that has a 3 axis accelerometer and a 3 axis gyroscope. The accelerometer measures changes in velocity along three perpendicular axes (x, y, and z), and the gyroscope detects changes in rotational position (pitch, roll, and yaw) along the same axes.
- A Global Navigation Satellite System (GNSS) receiver, which communicates with satellites to determine the sensor’s location on Earth.
- 200Hz 32-bit Position (Latitude, Longitude, Altitude)
- 400Hz 32-bit Velocity (Body X, Body Y, Body Z, and 2D Speed)
- 400Hz 32-bit Body Frame Acceleration (Gravity Removed) (X, Y, Z) with online acceleration bias compensation
- 400Hz 32-bit Angular Rate (X, Y, Z) with online gyro bias compensation
- 400Hz 16-bit Orientation (Roll, Pitch, Yaw (Degrees))
- 100Hz “MoTeC GPS” simulation option for integration with MoTeC M1 ECU applications with locked firmware (GT-R, Lamborghini, etc…)
- CNC aluminum enclosure with Deutsch ASL connection
What makes this sensor unique is its onboard sensor fusion algorithm. This sophisticated software combines the different measurements from the IMU and the GNSS to produce very accurate and fast updates on the sensor’s position, orientation, and movement.
The sensor fusion algorithm also corrects for biases (systematic errors) in the accelerometer and gyroscope measurements, ensuring even more accurate data.
Moreover, the device can calculate the velocities in the sensor’s (or the vehicle’s) own frame of reference, which can be extremely useful for understanding and controlling its movement.
Purpose:
- The main objective with this sensor is to put cutting edge, high performance sensor fusion algorithms into the hands of motorsport integrators and motorsport engineers without having to deal with sensor calibration, embedded systems, or understanding the sensitivity of MEMS IMU’s, specifically.
Functional Overview:
- The sensor fusion algorithm that runs on this sensor is an Extended Kalman Filter (EKF). An EKF is a filter that combines data from multiple sensors and provides a best guess estimate of the position, orientation, and velocity of the vehicle.
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