Methods and computerized machine for sequential bound estimation of target parameters in time-series data

摘要

Computerized sequential bounded estimation is performed on time-series data. Robust methods use bounds and probability distributions to estimate target parameters for time-dependent data, including but not limited to the location of objects or phenomena. Realistic prior probability distributions of pertinent variables are utilized, and time-dependent measurements and errors in measurements are received. Bounds and probability distributions can be obtained without making any assumption of linearity. The sequential methods used for location are applicable in other applications in which a function of the probability distribution is desired for variables that are related to measurements.