Title :
Estimation using subjective knowledge with tracking applications
Author :
Popoli, Robert ; Mendel, Jerry
Author_Institution :
Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
fDate :
7/1/1993 12:00:00 AM
Abstract :
Within the framework of classical estimation theory, there is no technically legitimate way to utilize knowledge that cannot be codified by either deterministic or strict probability models. The authors introduce a theoretically defensible approach called coordinated objective/subjective estimation (COSE) for the simultaneous incorporation of both objective and subjective knowledge in estimation. Also discussed is a technique, called heuristically constrained estimation (HCE) which is a particular interpretation of the Bayesian use of subjective priors. COSE, HCE, and classical maximum a posteriori probability (MAP) estimation are applied to a tracking problem
Keywords :
Bayes methods; estimation theory; heuristic programming; knowledge representation; probability; tracking; Bayesian method; coordinated objective/subjective estimation; data association; estimation theory; heuristically constrained estimation; maximum a posteriori probability; probability models; subjective knowledge; tracking; Assembly; Bayesian methods; Constraint optimization; Estimation theory; Frequency; Fuzzy sets; Fuzzy systems; Image processing; Knowledge engineering; Probability; Signal processing;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on