Product overview
The Beiwei Sensing BW-MINS225 is a packaged micro inertial navigation system for integration into unmanned aircraft, robotic equipment and other moving platforms. Its sensing architecture includes gyroscope and accelerometer functions, with CAN bus output for connection to host equipment. The enclosure measures 60 mm long, 59 mm wide and 29 mm high, providing a defined physical envelope for installation planning. Electrical integration requires a 9–36V DC supply, while the temperature-compensated operating range extends from -40℃ to +85℃.
Attitude measurement covers pitch through ±90º and roll through ±180º, with dynamic accuracy of 0.5° and static accuracy of 0.01°. Heading retention is specified as 0.3°/60s. Processing combines Kalman filtering with a bias-tracking algorithm for drift removal. The accelerometer range is ±1.8 g on each of three axes. Its bias-stability figures depend on the stated temperature and observation interval, while the gyroscope’s full-temperature bias stability is specified at 10 seconds and one standard deviation. These conditions distinguish the individual performance figures.
Specifications
| Specification | Value & conditions |
|---|---|
| Manufacturer and model | Beiwei Sensing BW-MINS225 micro inertial navigation system |
| Dynamic attitude accuracy | 0.5° |
| Static attitude accuracy | 0.01° |
| Attitude measurement range | Pitch ±90º; roll ±180º |
| Heading retention accuracy | 0.3°/60s |
| Gyroscope resolution | 0.01°/sec |
| Gyroscope bias stability | 20°/hFull temperature range; 10s, 1σ. |
| Angular random walk coefficient | Less than 0.1 °/√h |
| Accelerometer measurement range | ±1.8 gX, Y and Z axes. |
| Accelerometer bias stability over 100 seconds | 0.001mg25℃, 100s, 1σ. |
| Accelerometer bias stability over 10 seconds | 0.01mg25℃, 10s, 1σ. |
| Supply voltage | 9–36V DC |
| Output interface | CAN bus |
| Temperature range | -40℃ to +85℃Temperature compensated. |
| Dimensions | L60 × W59 × H29 mmPackaged product. |
| Bias tracking | Special bias-tracking algorithm for drift removal |
| Filtering | High-performance Kalman filtering algorithm |
| Applications | Unmanned boats and underwater vehicles; robots; platform stabilization; large ships; automated guided vehicles; automated and driverless driving; special-purpose vehicles; unmanned aircraft |
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