Sensor Fusion
Sensor fusion combines time-aligned measurements from multiple sensors into a more useful estimate of objects, motion, or the vehicle's surroundings.
Why systems combine measurements
A camera can contribute object appearance and lane geometry, radar can add range and radial velocity, and ultrasonic sensors can cover the near field. Fusion software associates measurements that may describe the same object and estimates properties such as position, speed, class, and confidence.
More sensors do not automatically create a better or redundant system. The inputs must be synchronized, geometrically calibrated, and handled according to their uncertainty. Shared obstructions, incorrect association, stale data, or software faults can still produce one wrong combined result.
Sensor fusion is therefore a processing method, not a sensor type and not a guarantee of safe behavior. Its value depends on the assigned function, sensor coverage, validation, and fallback strategy.
For fusion levels, uncertainty, disagreement, and the distinction between complementary sensing and redundancy, see Sensor Fusion: Combining Evidence, Not Just Sensors.