Research on the Relationship between Cramer-Rao Lower Bound and Location of Missing Data with Incomplete Measurements
不完全量测下Cramer-Rao下界与数据丢失位置的关系

Since the stochastic detection/miss sequences are introduced, Cramer-Rao lower bound (CRLB) for state estimation becomes stochastic. 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. It is a novel result that under certain conditions the modified CRLB is a monotonically decreasing function of LMD by use of Lyapunov inequality. Moreover, a pairs of upper and lower bounds of CRLB are also presented for a deterministic probability of detection. The numeral simulations reveal that the upper and lower bounds of CRLB approach the theoretic CRLB as the probability of detection increases.