Title :
A maximum likelihood approach to data association
Author :
Avitzour, Daniel
Author_Institution :
ELTA Electron. Ind., Ashdod, Israel
fDate :
4/1/1992 12:00:00 AM
Abstract :
An approach is presented to data association (DA) problems for which measurements are independent from scan to scan. It is demonstrated that maximum likelihood (ML) estimation of target parameters may be efficiently implemented by an EM iterative scheme. The algorithm is applied to multitarget trajectory estimation of constant-velocity targets from passive (bearing-only) sensors
Keywords :
estimation theory; iterative methods; probability; signal detection; signal processing; tracking; EM iterative scheme; constant-velocity targets; data association; maximum likelihood estimation; multitarget tracking; multitarget trajectory estimation; passive sensor; target parameters; Electronics industry; Iterative algorithms; Iterative methods; Maximum likelihood detection; Maximum likelihood estimation; Measurement uncertainty; Parameter estimation; Random variables; Sensor fusion; Time measurement;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
