Radar and optical track fusion using real data

The asynchronous fused Kalman filter (AFKF) is a useful tool for multisensor tracking, particularly when using dissimilar sensors such as radar and optical. Of particular interest is its tracking performance on real targets in real environments. Using radar and optical data collected from a cluttered, multitarget environment, we evaluate its performance and compare it to the single sensor Kalman filter under a range of adverse conditions