Generally, estimation performance of optic-electric tracking systems with intermittent observations is analyzed using extrapolating technology with thoughts of complete observations.

In order to evaluate the tracking performance of tracking systems with intermittent observations,a modified unbiased converted measurement Kalman Filtering(UCMKF) algorithm is presented by means of projection theorem.

The modified Riccati equation for discrete-time linear filtering with incomplete measurements

For the target tracking system on the background of such as environmental monitoring, air surveillance, maritime search and rescue, and navigational location-tracking, there exist incomplete measurements that probability of detection is less than unity owing to sensor detection ability limited and disturbance of environment meteorology.

Considering a correlation phenomenon between CRLB and location of missing data(LMD) for incomplete measurements systems in the case where the probability of detection is less than unity,the influence of LMD upon the CRLB is discussed for discrete-time random system.

Data Fusion Technology for Correction of Incomplete Trajectory Instrumentation with Missile Guidance Error Compensation Rule;