Optic-electric tracking system filter design based on posterior confidence residual test with intermittent observations

A key step of filter design for optic-electric tracking system with intermittent observations is to design residual test algorithm, and test probability of residual test algorithm influence estimate performance of tracking filter directly. A new residual test algorithm based on posterior confidence is presented in order to improve test probability of traditional residual test algorithm. The new algorithm firstly adds a test threshold based on traditional residual test algorithm, and then the residuals between the two thresholds can be fuzzed by means of fuzzy membership function and the likelihood probability of residuals can be obtained, and combined with the prior detection information, the posterior confidence of detection data can be calculated. Therefore the detection situation of tracking system can be determined based on the calculated posterior confidence. Moreover, with intermittent observations, a target tracking filter of unbiased converted measurement is designed based on the proposed residual test algorithm, and the Cramer-Rao low bounds (CRLB) of tracking system is also presented under the statistic significance. Monte-Carlo simulation results show that, with intermittent observations, the estimate performance of the designed target tracking filter can be significantly improved compared with that of traditional ones, when detection probability of tracking system is low, and the Root Mean Square of estimate Error (RMSE) of the designed tracking filter is close to the average of CRLB of the tracking system.