New results in optimizing surveillance system tracking and data correlation performance in dense multitarget environments

SONAR Systems and Underwater Signal Processing: Classic and Modern Approaches

“…Then it calculates the likelihood function for each track and the tracks with likelihoods less than a predefined threshold are deleted. In the nearest neighbor Kalman filter (NNKF) approach (Singer 1971, Sea 1971, Singer 1973, the contact that has the smallest statistical distance to the predicted target track is considered as a true target observation and the others are considered as clutter. The probabilistic data association filter (PDAF) introduced in (Bar-Shalom 1975), provides a suboptimal Bayesian approach for data association in the single target tracking problem.…”

Adaptive Tracking Algorithm for Tracking Air Targets with Search Radars

“…Some of the better known adaptive systems are adaptive antennas [1], phase-lock loops [2], and the Kaiman filter [3]. Recently there has been considerable interest in adaptive tracking systems [4][5][6][7][8][9][10][11][12]. Most of these adaptive systems use a feedback loop to adjust the parameters in the system.…”

Detection and Estimation of Signals in Uncertain Environments.

“…If the two operations of detection and estimation can be carried out in pa rallel or simultaneously , but in depen dently and th e two compon en ts Rã nd R E can be minimized separately , then the two problems are said to be uncoupled [ 4,5]. The detection procedure is carried out in the usual fashion but the estimator performance has to be optimized in the face of uncer tain ty as to th e signal presence.…”

“…The first function is referred to as sensor return-to-track correlation [3][4][5]. In the presence of multi ple targets a sensor return could originate from one of three possible sources (hypotheses).…”

“…. 1 33 has been studied in [1][2][3][4] by using a generalized cost function which reflects the mutual coupling between the joint operations .…”