Sensor Fusion
Definition
Sensor fusion combines multiple measurement sources into a common, as reliable as possible assessment.
The combination of measurements from multiple sensors to estimate state or environment more robustly or accurately.
Simply explained
As when parking, various cues are considered together instead of relying on just one sensor.
Why it matters in practice
The term helps to select, develop, evaluate AI systems in a well-founded manner and realistically assess their technical risks.
Example from business
Camera, radar, and motion sensors jointly provide a position estimate.
Limits and pitfalls
- Ignoring timestamps, calibration, correlated errors, or failed sensors.
Origin & history
Sensor fusion evolved from control engineering, navigation, and signal processing.
Use in mid-sized companies
- Possible example: Camera, radar, and motion sensors jointly provide a position estimate.
Frequently asked questions
What does sensor fusion mean?
The combination of measurements from multiple sensors to estimate state or environment more robustly or accurately. What errors should be avoided? Ignoring timestamps, calibration, correlated errors, or failed sensors.
Sources
Source checked on 10.10.2026. Editorial use cases are hypothetical; no evidence of real customer results.
Editorially reviewed on: