Abstract: The tracking performance of traditional optic-electric tracking systems degenerates significantly when there is a drop of detection probability with intermittent observation. This article introduces the innovative angle velocity measurements of elevation and azimuth into the traditional optic-electric tracking system, and then designs a filter for target tracking based on confidence weighted fusion with intermittent observation. First, a measurement model for the new type of optic-electric tracking system is built, and then using the nested conditioning method, the consistent estimate of the first two moments of the converted measurement errors is derived. Second, for the four different detection cases of position and velocity detection channels, four sub-filters are designed respectively whose confidences are calculated based on the detection cases of the channels, and then the output of the tracking filter is obtained by means of weighting the outputs of sub-filters with the corresponding confidences. Finally, the statistic average of Cramer-Rao low bound (CRLB) for the nonlinear tracking system is presentedMonte-Carlo simulation results show that, with intermittent observation, the performance of an optic-electric tracking system with angle velocity measurements can be significantly improved as compared with that of the traditional systems. Moreover, the root mean square of estimate error (RMSE) of the designed tracking filter is close to the average CRLB of nonlinear tracking systems.

Key words: state estimation, optic-electric tracking system, intermittent observation, angle velocity measurement, Cramer-Rao low bounds