Small Target Tracking Research Articles

An elaborated model of fly small-target tracking

Flies have the capability to visually track small moving targets, even across cluttered backgrounds. Previous computational models, based on figure detection (FD) cells identified in the fly, have suggested how this may be accomplished at a neuronal level based on information about relative motion between the target and the background. We experimented with the use of this "small-field system model" for the tracking of small moving targets by a simulated fly in a cluttered environment and discovered some functional limitations. As a result of these experiments, we propose elaborations of the original small-field system model to support stronger effects of background motion on small-field responses, proper accounting for more complex optical flow fields, and more direct guidance toward the target. We show that the elaborated model achieves much better tracking performance than the original model in complex visual environments and discuss the biological implications of our elaborations. The elaborated model may help to explain recent electrophysiological data on FD cells that seem to contradict the original model.

Performance of laser tracking of small targets during turbulence and beam jitter

Small target detection and tracking are important for laser radars in many applications such as laser weapons, directed infrared countermeasures (DIRCM), fire control, target recognition, and free-space laser communications. The detection and tracking performance depends on the mode of detection, SNR, target signal statistics, beam jitter, and turbulence induced irradiance variations. We show results of the root mean square (rms) tracking error versus SNR primarily for direct detection systems using a strong glint return. For the general case of a certain signal and noise probability density functions (pdf) it is hard to obtain analytical solutions for the mean and variances of the estimates for the rms tracking error. We have therefore used numerical simulations to illustrate how the pdf and SNR will affect the tracking accuracy. Gamma functions and other pdf's can be used to characterize the signal distributions to get a first hand on tracking performance. The results are presented as tracking errors versus the angular spot size of the laser beam in the tracking detector plane. We also investigate the beam optimization problem for target detection and "power in bucket," which is maximizing the laser energy at the target. We find that there are optimum beam sizes (w) versus the rms jitter () and that optimum w/ (minimizing the false alarm rate for a given detection probability Pd) typically fall in regions 1 to 3 depending on probability of detection and the representative pdf for the application in mind.