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\iteman{io-port 04162802}
\itemau{Sun, H.M.; Chiang, S.M.}
\itemti{Manoeuvring multitarget tracking method in cluttered environment.}
\itemso{Int. J. Syst. Sci. 21, No.12, 2469-2487 (1990).}
\itemab
Summary: A method for tracking a manoeuvring multitarget in a cluttered environment is presented. The clutter or false alarms are assumed to occur uniformly and to be independently distributed. The algorithm is performed by taking a sliding window of length uT (T is the sampling time) at time K. Instead of solving a large problem, the entire set of targets and measurements is divided into clusters so that a number of smaller problems are solved independently. When a set of measurements is received, we form a new data-association hypothesis for the set of measurements lying in the validation gates with each cluster from time $K-u+1$ to K. The probability of each track history is computed, and then by choosing the largest of these histories we perform the target measurement updated with the adaptive state estimator. Meanwhile, the covariance-matching technique is adopted so that the accuracy of the adaptive state estimator will be improved. Simulation has shown the effectiveness of the tracking algorithm.
\itemrv{~}
\itemcc{}
\itemut{tracking a manoeuvring multitarget; cluttered environment; covariance- matching technique; adaptive state estimator}
\itemli{doi:10.1080/00207729008910565}
\end